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  • Articles  (923)
  • Blackwell Publishing Ltd
  • American Institute of Physics (AIP)
  • Computer Science  (923)
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  • 1
    Electronic Resource
    Electronic Resource
    An adaptive learning algorithm for a wavelet neural network (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: An optimal online learning algorithm of a wavelet neural network is proposed. The algorithm provides not only the tuning of synaptic weights in real time, but also the tuning of dilation and translation factors of daughter wavelets. The algorithm has both tracking and smoothing properties, so the wavelet networks trained with this algorithm can be efficiently used for prediction, filtering, compression and classification of various non-stationary noisy signals.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00314.x
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  • 2
    Electronic Resource
    Electronic Resource
    Strategies for preventing defection based on the mean time to defection and their implementations on a self-organizing map (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Customer retention is a critical issue for the survival of any business in today's competitive marketplace. In this paper, we propose a dynamic procedure utilizing self-organizing maps and a Markov process for detecting and preventing customer defection that uses data of past and current customer behavior. The basic concept originates from empirical observations that identified that a customer has a tendency to change behavior (i.e. trim-out usage volumes) before eventual withdrawal and defection. Our explanatory model predicts when potential defectors are likely to withdraw. Two strategies are suggested to respond to the question of where to lead potential defectors for the next stage, based on anticipating when the potential defector will leave. Our model predicts potential defectors with little deterioration of prediction accuracy compared with that of the multilayer perceptron neural network and decision trees. Moreover, it performs reasonably well in a controlled experiment using an online game.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00317.x
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  • 3
    Electronic Resource
    Electronic Resource
    Diary (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00319.x
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  • 4
    Electronic Resource
    Electronic Resource
    News (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00318.x
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  • 5
    Electronic Resource
    Electronic Resource
    A Web-enabled product definition and customization system for product conceptualization (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Owing to rapidly changing customer needs and much shorter product life cycles, for developing a successful product it is imperative to employ more efficient and flexible approaches for product conceptualization. To meet this demand, a Web-enabled product definition and customization system (PDCS) is proposed, from a design-knowledge-handling viewpoint, in this paper. It comprises two phases, namely product definition based on the laddering technique and a novel design knowledge hierarchy, and product customization based on an integrated methodology of conjoint analysis and Kohonen association techniques. Basically, this system is a method of conducting design decision-making via customer involvement, i.e. a strategy for transforming customer preference into a specific product concept. A case study on wood golf club design is used to illustrate and validate the proposed Web-enabled PDCS.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00315.x
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  • 6
    Electronic Resource
    Electronic Resource
    Developments of fuzzy PID controllers (2005)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 22 (2005), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper describes the development and tuning methods for a novel self-organizing fuzzy proportional integral derivative (PID) controller. Before applying fuzzy logic, the PID gains are tuned using a conventional tuning method. At supervisory level, fuzzy logic readjusts the PID gains online. In the first tuning method, fuzzy logic at the supervisory level readjusts the three PID gains during the system operation. In the second tuning method, fuzzy logic only readjusts the proportional PID gain, and the corresponding integral and derivative gains are readjusted using the Ziegler–Nichols tuning method while the system is in operation. For the compositional rule of inferences in the fuzzy PID and the self-organizing fuzzy PID schemes two new approaches are introduced: the min implication function with the mean of maxima defuzzification method, and the max-product implication function with the centre of gravity defuzzification method. The fuzzy PID controller, the self-organizing fuzzy PID controller and the PID controller are all applied to a non-linear revolute-joint robot arm for step input and path tracking experiments using computer simulation. For the step input and path tracking experiments, the novel self-organizing fuzzy PID controller produces a better output response than the fuzzy PID controller; and in turn both controllers exhibit better process output than the PID controller.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2005.00316.x
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  • 7
    Electronic Resource
    Electronic Resource
    The application of a fuzzy-rule-based system in an exposition of the antecedents of sedge warbler song flight (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract:  The utilization of a fuzzy aspect within data analysis attempts to move from a quantitative to a more qualitative investigative environment. As such, this may allow the more non-quantitative researchers results they can use, based on sets of linguistic terms. In this paper an inductive fuzzy decision tree approach is utilized to construct a fuzzy-rule-based system for the first time in a biological setting. The specific biological problem considered attempts to identify the antecedents (conditions in the fuzzy decision rules) which characterize the length of song flight of the male sedge warbler when attempting to attract a mate. Hence, for a non-quantitative investigator the resultant set of fuzzy rules allows an insight into the linguistic interpretation on the relationship between associated characteristics and the respective song flight duration.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00258.x
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  • 8
    Electronic Resource
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    News (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00262.x
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  • 9
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    CRAS-CBR: Internal control risk assessment system using case-based reasoning (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Information technology and the Internet have been major drivers for changes in all aspects of business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist certain difficulties, however, with current audit procedures especially for the assessment of the level of control risk. This assessment is primarily based on the auditors' professional judgment and experiences, not on objective rules or criteria.To overcome these difficulties, we propose a prototype decision support model named CRAS-CBR using case-based reasoning to support auditors in making their professional judgment on the assessment of the level of control risk of the general accounting system in the manufacturing industry.To validate the performance, we compare our proposed model with benchmark performances in terms of classification accuracy for the level of control risk. Our experimental results show that CRAS-CBR outperforms a statistical model and staff auditor performance in average hit ratio.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00260.x
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  • 10
    Electronic Resource
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    Categorial expert systems (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Expert systems can be used to determine some objects or consequences from uncertain knowledge by hierarchical categorization. Categorical representation is psychologically motivated and also offers an explanation of how to deal with uncertain knowledge based on counting during approximate reasoning. It is an alternative to other well-known uncertainty calculi. A knowledge base which is used during approximate reasoning is represented by a taxonomical arrangement of verbal categories. Priming eases the formation of the final hypothesis, as more exact possible hypotheses are formed. The approximate reasoning is demonstrated on an expert system ‘Jurassic’ from the field of paleontology for the determination of a dinosaur species. It helps the paleontologist to determine creatures from uncertain knowledge. The system is composed of 423 rules arranged in a directed acyclic graph with a depth of 5. This knowledge is represented by a taxonomical arrangement of verbal categories represented by associative memories.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00261.x
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  • 11
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    An agent-oriented and knowledge-based system for strategic e-procurement (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract:  This paper presents an agent-oriented and knowledge-based system (AOKBS) for strategic e-procurement. The AOKBS has been designed to capture and leverage the knowledge of an enterprise to generate dynamic business rules by which an effective procurement strategy can be generated based on enterprise needs and the analysis of relevant market conditions. The performance and practices of the suppliers can also be evaluated and captured continuously, respectively, by the AOKBS. Artificial intelligence technologies such as case-based reasoning and agent technology are incorporated for decision analysis. A prototype e-procurement system has been built and implemented successfully with a multinational manufacturer.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00259.x
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  • 12
    Electronic Resource
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    Diary (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00263.x
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  • 13
    Electronic Resource
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    A wavelet neural network for the detection of heart valve diseases (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: An expert system is presented for interpretation of the Doppler signals of heart valve diseases based on pattern recognition. We deal in particular with the combination of feature extraction and classification from measured Doppler signal waveforms at the heart valve using Doppler ultrasound. A wavelet neural network model developed by us is used. The model consists of two layers: a wavelet layer and a multilayer perceptron. The wavelet layer used for adaptive feature extraction in the time–frequency domain is composed of wavelet decomposition and wavelet entropy. The multilayer perceptron used for classification is a feedforward neural network. The performance of the developed system has been evaluated in 215 samples. The test results show that this system is effective to detect Doppler heart sounds. The classification rate averaged 91% correct for 123 test subjects.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00219
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  • 14
    Electronic Resource
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    Diary (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00224
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  • 15
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    Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Just like rough set theory, fuzzy set theory addresses the topic of dealing with imperfect knowledge. Recent investigations have shown how both theories can be combined into a more flexible, more expressive framework for modelling and processing incomplete information in information systems. At the same time, intuitionistic fuzzy sets have been proposed as an attractive extension of fuzzy sets, enriching the latter with extra features to represent uncertainty (on top of vagueness). Unfortunately, the various tentative definitions of the concept of an ‘intuitionistic fuzzy rough set’ that were raised in their wake are a far cry from the original objectives of rough set theory. We intend to fill an obvious gap by introducing a new definition of intuitionistic fuzzy rough sets, as the most natural generalization of Pawlak's original concept of rough sets.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00250
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  • 16
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    Acquisition of hierarchy-structured probabilistic decision tables and rules from data (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The paper is concerned with the creation of predictive models from data within the framework of the variable precision rough set model. It is focused on two aspects of the model derivation: computation of uncertain, in general, rules from information contained in probabilistic decision tables and forming hierarchies of decision tables with the objective of reduction or elimination of decision boundaries in the resulting classifiers. A new technique of creation of a linearly structured hierarchy of decision tables is introduced and compared to tree-structured hierarchy. It is argued that the linearly structured hierarchy has significant advantages over tree-structured hierarchy.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00255
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  • 17
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    Rough sets and maintenance in a production line (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The great volume of information used/obtained in industry nowadays produces the need for systems that are helpful in decision-making. An area of special interest, because of its influence on productive capacity, is maintenance, where the great quantity of influential variations and available facts (including real time) make the analysis almost impossible. Using the concept of rough sets, we present a comprehensive (but real) application where the information system is reduced so as to get a minimum subset of attributes without loss of quality; a set of nine decision rules is obtained.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00251
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  • 18
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    Probabilistic approaches to rough sets (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Probabilistic approaches to rough sets in granulation, approximation and rule induction are reviewed. The Shannon entropy function is used to quantitatively characterize partitions of a universe. Both algebraic and probabilistic rough set approximations are studied. The probabilistic approximations are defined in a decision-theoretic framework. The problem of rule induction, a major application of rough set theory, is studied in probabilistic and information-theoretic terms. Two types of rules are analyzed: the local, low order rules, and the global, high order rules.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00253
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  • 19
    Electronic Resource
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    News (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00256
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  • 20
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    Book Review: (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Book reviewed:Adrian A. Hopgood, Intelligent Systems for Engineers and Scientists
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00222
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  • 21
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    A rough set theory based method for anomaly intrusion detection in computer network systems (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Intrusion detection is important in the defense-in-depth network security framework. This paper presents an effective method for anomaly intrusion detection with low overhead and high efficiency. The method is based on rough set theory to extract a set of detection rules with a minimal size as the normal behavior model from the system call sequences generated during the normal execution of a process. It is capable of detecting the abnormal operating status of a process and thus reporting a possible intrusion. Compared with other methods, the method requires a smaller size of training data set and less effort to collect training data and is more suitable for real-time detection. Empirical results show that the method is promising in terms of detection accuracy, required training data set and efficiency.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00249
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  • 22
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    A rough set approach to knowledge reduction based on inclusion degree and evidence reasoning theory (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The theory of rough sets is an extension of set theory for studying intelligent systems characterized by insufficient and incomplete information. We discuss the basic concept and properties of knowledge reduction based on inclusion degree and evidence reasoning theory, and propose a knowledge discovery approach based on inclusion degree and evidence reasoning theory.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00254
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  • 23
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    Diary (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00257
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  • 24
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    Providing Websites with capabilities of one–to–one marketing (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: A formidable synergy can be obtained by putting expert system technology into the Internet. The modern trend of embedding expert systems into Websites turns out to be very promising, in particular for the field of marketing via the Web. The last two years have seen a growing interest in providing Websites with suitable embedded expert systems for one–to–one marketing. One–to– one marketing means marketing in a personalized way, i.e. marketing in a way that is adaptive to the personal needs of the user. A basic feature of this marketing framework consists in personalized prioritizing of news, i.e. presenting information in an order that is relevant to the specific needs of the current user. If the personalized prioritizing of news is a very useful feature in wired Web, it becomes essential in wireless Web, the promising next generation of the Web.The paper presents a general methodology for personalized prioritizing of news. The methodology integrates decision theory with a deep–knowledge–based user model (i.e. causal knowledge linking user preferences to user goals). The deep–knowledge model of the user is a source of power of the methodology because it allows the system to know (and possibly explain) why the user acts the way he/she acts. Another relevant aspect of the methodology is that the burden of personalization is not placed on the user, and in fact the user does not have to declare his/her needs or interests or goals: they are automatically inferred from his/her profile data. In order to investigate the ideas underlying the proposal, a methodology example has been implemented in a prototype and then tested on real cases in the context of a supercomputing portal.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00220
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  • 25
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    On a responsive replenishment system: a fuzzy logic approach (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00221
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  • 26
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    News (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00223
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  • 27
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    Rough sets: current and future developments (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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    URL: http://dx.doi.org/10.1111/1468-0394.00248
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  • 28
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    Knowledge acquisition in incomplete fuzzy information systems via the rough set approach (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Machine learning can extract desired knowledge from training examples and ease the development bottleneck in building expert systems. Most learning approaches derive rules from complete and incomplete data sets. If attribute values are known as possibility distributions on the domain of the attributes, the system is called an incomplete fuzzy information system. Learning from incomplete fuzzy data sets is usually more difficult than learning from complete data sets and incomplete data sets. In this paper, we deal with the problem of producing a set of certain and possible rules from incomplete fuzzy data sets based on rough sets. The notions of lower and upper generalized fuzzy rough approximations are introduced. By using the fuzzy rough upper approximation operator, we transform each fuzzy subset of the domain of every attribute in an incomplete fuzzy information system into a fuzzy subset of the universe, from which fuzzy similarity neighbourhoods of objects in the system are derived. The fuzzy lower and upper approximations for any subset of the universe are then calculated and the knowledge hidden in the information system is unravelled and expressed in the form of decision rules.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00252
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  • 29
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    Applications of artificial neural networks to the nonlinear combination of forecasts (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper proposes artificial neural networks (ANN) as a tool for nonlinear combination of forecasts. In this study, three forecasting models are used for individual forecasts, and then two linear combining methods are used to compare with the ANN combining method. The comparative experiment using real-world data shows that the prediction by the ANN method outperforms those by linear combining methods. The paper suggests that the ANN method can be used as an alternative to conventional linear combining methods to achieve greater forecasting accuracy.
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00119.x
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    Book Reviews (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The Handbook of Brain Theory and Neural Networks Michael A. Arbib (Ed.)Virtual Reality Systems John VinceThe Uncertain Reasoner's Companion J. B. Paris
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    News (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00188.x
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    Book Reviews (1996)
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Open Distributed Systems Jon Crowcrofi
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00128.x
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    A generic, object-oriented case-knowledge representation scheme, and its integration into a wider information management scenario (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: A knowledge base management system (KBMS) realises a combination of techniques found in database management systems and knowledge-based systems. At the data model and knowledge representation level, many systems of this kind constitute a marriage of the relational data model and the rule-based reasoning. Experience has shown that either approach is restricted in the way it can express the demanding information and knowledge structures required for applications like decision support systems. Two new technologies offer an exciting new integrated approach to knowledge management. Object-oriented database management systems (OODBMS) provide an object model that supports powerful abstraction mechanisms to facilitate the modelling of highly structured information. Whereas case-based reasoning (CBR) systems are knowledge bases which organise their capabilities around a memory of past cases and the notion of similarity. Both types of system are built upon two fundamental concepts: 1) the retrieval of entities with potentially complex structure, called objects in the former, and cases in the latter type of system; 2) the organisation of those entities in collections with common characteristics. In an OODBMS such collections are termed extents, and in CBR they are usually called categories. In either system, the conceptual meta notion to represent both, objects as well as extents, and cases as well as categories, is the class.Revolving around a Conceptual Case Class and extending a standard object model, this paper proposes a novel and general approach to represent case-knowledge and to build KBMSs. The work presented here is a spin-off of the design of an object query language within the ESPRIT project Lynx.
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    Standardising the elimination of unnecessary data from interview transcripts for the purposes of knowledge-based systems — a case study (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
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    Notes: Abstract: Although knowledge elicitation, the process of extracting knowledge from human experts to be incorporated into a knowledge-based system, has been the subject of some notable studies, less attention has been paid to the methods of analysing the raw data once it has been extracted from the expert. When knowledge elicitation sessions are interview-based, the resultant form of raw data is usually a transcript of the interviewee's utterances. This paper describes an investigation into the preliminary stage of analysing such transcripts. It outlines the development of an approach to eliminate unnecessary detail from interview transcripts, thus enabling attention to be focused upon the remaining, more relevant data via a simple technique based upon cheap and readily available technology. The paper then outlines a rapid-prototyping approach for evaluating this method, the results of which were felt to be very encouraging.
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00279.x
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    Knowledge types: a practical approach to guide knowledge engineering in domains of building design (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper presents experiences and findings achieved through several expert system projects in domains of technical buiding design. The main focus is on knowledge acquisition and knowledge decomposition. Different approaches are presented and discussed. Four types of knowledge are presented: object knowledge, performance knowledge, event knowledge and metaknowledge, and the applicability of this classification to building design is justified. The paper includes a listing of experiences gained by real world testing of an expert system, and finally we outline guidelines to knowledge engineering in the domain of technical building
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00186.x
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    NOTE OF APPRECIATION FROM THE EDITORS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00274.x
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    COMPUTATION OF BEST BOUNDS OF PROBABILITIES FROM UNCERTAIN DATA (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: An uncertainty reasoning method is presented in this article. The method can be used to compute from a given set of conditional probabilities the best lower bounds and the best upper bounds of those conditional probabilities that are not explicitly provided. The computation of the best upper(lower) bound of such a conditional probability relies on solution of a linear programming problem. Some reduction techniques are proposed in this article to improve the efficiency of our uncertainty reasoning method. As illustrated in Section 4.3, for many uncertainty reasoning problems in medical diagnosis, by using our reduction techniques, the best range of a conditional probability, which is specified by a lower bound and an upper bound, can be computed in polynomial time in terms of the number of basic events involved in the reasoning.
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    EFFICIENT TEMPORAL REASONING IN THE CACHED EVENT CALCULUS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
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    Topics: Computer Science
    Notes: This article deals with the problem of providing Kowalski and Sergot's event calculus, extended with context dependency, with an efficient implementation in a logic programming framework. Despite a widespread recognition that a positive solution to efficiency issues is necessary to guarantee the computational feasibility of existing approaches to temporal reasoning, the problem of analyzing the complexity of temporal reasoning programs has been largely overlooked. This article provides a mathematical analysis of the efficiency of query and update processing in the event calculus and defines a cached version of the calculus that (i) moves computational complexity from query to update processing and (ii) features an absolute improvement of performance, because query processing in the event calculus costs much more than update processing in the proposed cached version.
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    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00267.x
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    INTERACTIVE SEMANTIC ANALYSIS OF TECHNICAL TEXTS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Sentence syntax is the basis for organizing semantic relations in TANKA, a project that aims to acquire knowledge from technical text. Other hallmarks include an absence of precoded domain-specific knowledge; significant use of public-domain generic linguistic information sources; involvement of the user as a judge and source of expertise; and learning from the meaning representations produced during processing. These elements shape the realization of the TANKA project: implementing a trainable text processing system to propose correct semantic interpretations to the user. A three-level model of sentence semantics, including a comprehensive Case system, provides the framework for TANKA's representations. Text is first processed by the DIPETT parser, which can handle a wide variety of unedited sentences. The semantic analysis module HAIKU then semi-automatically extracts semantic patterns from the parse trees and composes them into domain knowledge representations. HAIKU's dictionaries and main algorithm are described with the aid of examples and traces of user interaction. Encouraging experimental results are described and evaluated.
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    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00263.x
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    SOLVING NINE MEN'S MORRIS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The game of Nine Men's Morris is a draw. We obtained this result using a combination of endgame databases (1010 states) and search. Our improved algorithm for computing endgame databases allowed the game to be solved on a personal computer. Other games have been solved using knowledge-based methods to dramatically prune the search tree. Nine Men's Morris does not seem to profit from such methods, making it the first nontrivial game solved in which almost the entire state space has to be considered.
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    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00251.x
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    VALIDATION OF FIRST-ORDER RULE-BASED SYSTEMS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Knowledge base validation and knowledge base refinement aim to help the expert to improve an existing knowledge base. They deal with the final knowledge acquisition phase and rely on a quality measurement of an existing knowledge base. We present our approach to knowledge base refinement, which is based on results in the domain of knowledge base validation. Our approach is based on a general consistency definition of a knowledge base and on a study of causes of knowledge base inconsistency. Our approach relies significantly on a differentiation of sure and expert knowledge in the knowledge base. We have implemented a system that has two phases: one computational phase decides on the consistency of a knowledge base, and, if necessary, a second phase helps the expert to interactively update the knowledge base. We present some related work in the domain. We illustrate the use of our system with an example.
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    DOMAIN-INDEPENDENT TEMPORAL REASONING WITH RECURRING EVENTS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Numerous examples of temporal reasoning involve a process of abstraction from the number of times an event is to occur or the number of times events stand in a temporal relation. For example, scheduling a recurring event such as one's office hours may consider things like the relative temporal ordering of the office hours and a number of other events in a given work day. The number of times office hours will actually be held may be unknown, even irrelevant, at the time of scheduling them. The objective of this article is to formulate a domain-independent framework for reasoning about recurring events and their relations. To achieve this end, we propose an ontology of recurrence based on the model-theoretic structure underlying collective predication using plural noun phrases. We offer a calculus of binary temporal relations for temporal collections based on a well-defined transformation of interval temporal relations into recurrence relations. Finally, we describe a reasoning framework based on manipulating knowledge stored in temporal relation networks, which is in turn a specialization of the CSP (constraint satisfaction problem) framework. The reasoner manipulates recurrence relations in the network to determine the network's consistency or to generate scenarios.
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    LOCALIZED TEMPORAL REASONING USING SUBGOALS AND ABSTRACT EVENTS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We are concerned with temporal reasoning problems where there is uncertainty about the order in which events occur. The task of temporal reasoning is to derive an event sequence consistent with a given set of ordering constraints to achieve a goal. Previous research shows that the associated decision problems are hard even for very restricted cases. In this article, we investigate locality in event ordering and causal dependencies. We present a localized temporal reasoning algorithm that uses subgoals and abstract events to exploit locality. The computational efficiency of our algorithm for a problem instance is quantified by the inherent locality in the instance. We theoretically demonstrate the substantial improvement in performance gained by exploiting locality. This work provides solid evidence of the usefulness of localized reasoning in exploiting locality.
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    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00270.x
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    ON TEMPORAL DEDUCTIVE DATABASES (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This article introduces a temporal deductive database system featuring a logic programming language and an algebraic front-end. The language, called Temporal DATALOG, is an extension of DATALOG based on a linear-time temporal logic in which the flow of time is modeled by the set of natural numbers. Programs of Temporal DATALOG are considered as temporal deductive databases, specifying temporal relationships among data and providing base relations to the algebraic front-end. The minimum model of a given Temporal DATALOG program is regarded as the temporal database the program models intensionally. The algebraic front-end, called TRA, is a point-wise extension of the relational algebra upon the set of natural numbers. When needed during the evaluation of TRA expressions, slices of temporal relations over intervals can be retrieved from a given temporal deductive database by bottom-up evaluation strategies.A modular extension of Temporal DATALOG is also proposed, through which temporal relations created during the evaluation of TRA expressions may be fed back to the deductive part for further manipulation. Modules therefore enable the algebra to have full access to the deductive capabilities of Temporal DATALOG and to extend it with nonstandard algebraic operators. This article also shows that the temporal operators of TRA can be simulated in Temporal DATALOG by program clauses.
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    GO-MOKU SOLVED BY NEW SEARCH TECHNIQUES (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Many decades ago, Japanese professional Go-Moku players stated that Go-Moku (five-in-a-row on a horizontally placed 15×15 board) is a won game for the player to move first. So far, this claim has never been substantiated by (a tree of) variations or by a computer program. Meanwhile, many variants of Go-Moku with slightly different rules have been developed. This paper shows that for two common variants, the game-theoretical value has been established.Moreover, the Go-Moku program Victoria is described. It uses two new search techniques: threat-space search and proof-number search. One of the results is that Victoria is bound to win against any (optimal) counterplay if it moves first. Furthermore, it achieves good results as a defender against nonoptimally playing opponents. In this contribution we focus on threat-space search and its advantages compared to conventional search algorithms.
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    A PLANNING APPROACH TO DECLARER PLAY IN CONTRACT BRIDGE (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Although game-tree search works well in perfect-information games, it is less suitable for imperfect-information games such as contract bridge. The lack of knowledge about the opponents’ possible moves gives the game tree a very large branching factor, making it impossible to search a significant portion of this tree in a reasonable amount of time.This paper describes our approach for overcoming this problem. We represent information about bridge in a task network extended to represent multi-agency and uncertainty. Our game-playing procedure uses this task network to generate game trees in which the set of alternative choices is determined not by the set of possible actions, but by the set of available tactical and strategic schemes.We have tested this approach on declarer play in the game of bridge, in an implementation called Tignum 2. On 5000 randomly generated notrump deals, Tignum 2 beat the strongest commercially available program by 1394 to 1302, with 2304 ties. These results are statistically significant at the α= 0.05 level. Tignum 2 searched an average of only 8745.6 moves per deal in an average time of only 27.5 seconds per deal on a Sun SPARCstation 10. Further enhancements to Tignum 2 are currently underway.
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    EVENT TRACKING IN A DYNAMIC MULTIAGENT ENVIRONMENT (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In a dynamic, multiagent environment, an automated intelligent agent is often faced with the possibility that other agents may instigate events that hinder or help the achievement of its own goals. To act intelligently in such an environment, an automated agent needs an event tracking capability to continually monitor the occurrence of such events and the temporal relationships among them. This capability enables an agent to infer the occurrence of important unobserved events as well as to obtain a better understanding of the interaction among events. This article focuses on event tracking in one complex and dynamic multiagent environment: the air-combat simulation environment. It analyzes the challenges that an automated pilot agent must face when tracking events in this environment. This analysis reveals three new issues that have not been addressed in previous work in this area: (i) tracking events generated by agents’ flexible and reactive behaviors, (ii) tracking events in the context of continuous agent interactions, and (iii) tracking events in real time. This article proposes one solution to address these issues. One key idea in this solution is that the (architectural) mechanisms that an agent employs in generating its own flexible and reactive behaviors can be used to track other agents’ flexible and reactive behaviors in real time. A second key idea is the use of a world-centered representation for modeling agent interactions. The solution is demonstrated using an implementation of an automated pilot agent.
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    GENERAL GAME-PLAYING AND REINFORCEMENT LEARNING (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper provides a blueprint for the development of a fully domain-independent single-agent and multiagent heuristic search system. It gives a graph-theoretic representation of search problems based on conceptual graphs and outlines two different learning systems. One, an “informed learner”, makes use of the graph-theoretic definition of a search problem or game in playing and adapting to a game in the given environment. The other, a “blind learner”, is not given access to the rules of a domain but must discover and then exploit the underlying mathematical structure of a given domain. Relevant work of others is referenced within the context of the blueprint.To illustrate further how one might go about creating general game-playing agents, we show how we can generalize the understanding obtained with the Morph chess system to all games involving the interactions of abstract mathematical relations. A monitor for such domains has been developed, along with an implementation of a blind and informed learning system known as Morphll. Performance results with MorphK are preliminary but encouraging and provide a few more data points with which to understand and evaluate the blueprint.
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    PERFECT RECALL AND PRUNING IN GAMES WITH IMPERFECT INFORMATION (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Games with imperfect information are an interesting and important class of games. They include most card games (e.g., bridge and poker) as well as many economic and political models. Here we investigate algorithms for findi ng the simplest form of a solution (a pure-strategy equilibrium point) to imperfect information games expressed in their extensive (game tree) form. We introduce to the artificial intelligence community a classic algorithm, due to Wilson, that solves one-player games with perfect recall. Wilson's algorithm, which we call iMP-minimax, runs in time linear in the size of the game-tree searched. In contrast to Wilson's result, Koller and Meggido have shown that finding a pure-strategy equilibrium point in one-player games without perfect recall is NP-hard. Here, we provide another contrast to Wilson's result–we show that in games with perfect recall but more than one player, finding a pure-strategy equilibrium point, given that such an equilibrium point exists, is NP-hard.Our second contribution is to present a pruning technique for Wilson's IMP-minimax algorithm to make the latter more tractable. We call this new algorithm IMP-alpha-beta. We provide a theoretical framework (model) and analyze IMP-alpha-beta in that model. IMP-alpha-beta is of direct value for one-player, perfect-recall games. It also has strong potential for other imperfect information games, as it is a natural (but as yet untested) heuristic in those cases.
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    A STRATEGIC METAGAME PLAYER FOR GENERAL CHESS-LIKE GAMES (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper introduces METAGAMER, the first program designed within the paradigm of Metagame-playing (Metagame). This program plays games in the class of symmetric chess-like games, which includes chess, Chinese chess, checkers, draughts, and Shogi. METAGAMER takes as input the rules of a specific game and analyzes those rules to construct an efficient representation and an evaluation function for that game; they are used by a generic search engine. The strategic analysis performed by METAGAMER relates a set of general knowledge sources to the details of the particular game. Among other properties, this analysis determines the relative value of the different pieces in a given game. Although METAGAMER does not learn from experience, the values resulting from its analysis are qualitatively similar to values used by experts on known games and are sufficient to produce competitive performance the first time METAGAMER plays a new game. Besides being the first Metagame-playing program, this is the first program to have derived useful piece values directly from analysis of the rules of different games. This paper describes the knowledge implemented in METAGAMER, illustrates the piece values METAGAMER derives for chess and checkers, and discusses experiments with METAGAMER on both existing and newly generated games.
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    A comparison of knowledge elicitation methods (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper describes a computer based approach to comparing data obtained for Knowledge Based Systems via established but very varied knowledge elicitation (KE) techniques. It describes not only the detailed comparison of different KE methods (in this case ‘scaling’ and ‘non-scaling’) but also investigates the use of ‘demonstration’ or ‘evaluation’ systems, as a variation on the more established rapid prototyping approaches to the elicitation and evaluation of knowledge for KBS construction, in this case by focusing upon the quality and relevance of the elicited knowledge from the perspective of the expert himself. Preliminary results from the study reported here suggest that non-scaling methods produce a greater amount of raw data than scaling methods, and that this data is less likely to require correction or modification for inclusion within a Knowledge Based System. However, the results also indicate that non-scaling derived data is more likely than scaling derived data data to be rejected outright.
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    An interactive fault diagnosis expert system for a helpdesk application (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper presents work on an interactive fault diagnosis expert system for a helpdesk application. A knowledge representation and inference algorithm is proposed to satisfy three design specifications: (1) no parallel event exists in human fault reporting; (2) the diagnostic sequence is unpredictable, and (3) the inference engine is passive in an event-driven environment. A lattice data structure is designed for knowledge representation, which is generated automatically from a script of decision rules. The inference engine works in a transaction-like style by prompting and responding to the user according to the knowledge in the lattice. It can explicitly guide the inference sequence, as well as respond to ad hoc input from the user.
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    A constructive design method for two-layer perceptrons and its applicatio to the design of modular neural networks (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: A multilayer perceptron is known to be capable of approximating any smooth function to any desired accuracy if it has a sufficient number of hidden neurons. But its training, based on the gradient method, is usually a time consuming procedure that may converge toward a local minimum, and furthermore its performance is greatly influenced by the number of hidden neurons and their initial weights. Usually these crucial parameters are determined based on the trial and error procedure, requiring much experience on the designer's part.In this paper, a constructive design method (CDM) has been proposed for a two-layer perceptron that can approximate a class of smooth functions whose feature vector classes are linearly separable. Based on the analysis of a given data set sampled from the target function, feature vectors that can characterize the function‘well’are extracted and used to determine the number of hidden neurons and the initial weights of the network. But when the classes of the feature vectors are not linearly separable, the network may not be trained easily, mainly due to the interference among the hyperplanes generated by hidden neurons. Next, to compensate for this interference, a refined version of the modular neural network (MNN) has been proposed where each network module is created by CDM. After the input space has been partitioned into many local regions, a two-layer perceptron constructed by CDM is assigned to each local region. By doing this, the feature vector classes are more likely to become linearly separable in each local region and as a result, the function may be approximated with greatly improved accuracy by MNN. An example simulation illustrates the improvements in learning speed using a smaller number of neurons.
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    Importance of information pre-processing in the improvement of neural network results (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper compares the success ratio of certain topologies when their input data are changed through different pre-processing methods. It begins with the database description, and it shows some different kinds of pre-processing that will be applied and the necessary modifications to the input layer of the network. The process is carried out using four networks with supervised learning (Standard Backpropagation, Quick propagation, Resilient Propagation and Backpropagation with Momentum) and two with unsupervised learning (ART 1 and Dynamic Learning Vector Quantization).
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    Process factors in knowledge acquisition (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Knowledge acquisition (KA) is often characterised as a crucial bottleneck in the development of expert system applications. General definitions of KA view it as a collection of subprocesses such as elicitation, analysis and representation, but in actual practice, each KA occurrence may involve one or all of these subprocesses in varying sequences and combinations. No model or framework currently exists for describing the many possible variations in KA processes as they actually occur. This article presents a new way of characterising knowledge acquisition processes that is not tied to one particular technique or approach to KA. Three nested levels are proposed to characterise the many possible variations and combinations of KA dynamics: the process, episode and transaction levels of analysis. Each of these is further delineated in a top-down manner. Not only does this scheme provide a fairly comprehensive means for viewing KA dynamics as a whole, but it suggests several factors that have heretofore drawn little research attention. The suggested constructs capture more accurately what actually occurs in the practice of KA. In so doing they also provide the foundation for structuring future research into how KA processes may unfold.
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    An expert system for unit commitment and power demand prediction using fuzzy logic and neural networks (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The paper discusses the implementation of a fuzzy logic and artificial neural networks approach to providing a structural framework for the representation, manipulation and utilisation of data and information concerning prediction of power demand and generation commitments. An algorithm has been implemented and trained to predict the power demand at each load point on an hourly basis. The neural network is then implemented to supply the brute force necessary to accommodate the large amount of sensory data to provide the initial evaluation of the generation units to be committed. Results of the fuzzy model show a reasonable correspondence with the actual power demand. A standard deviation error for an hourly based prediction is limited to 4.4. Further refinement of the fuzzy model may produce further improvements. Implementation of artificial neural networks for scheduling an hourly unit commitment based on load demands is also discussed The backpropagation technique based on the I/O mapping method has been chosen for structuring the neural network. Geographically related load points and generating units are clustered into groups. Grouping has significantly reduced the number of inputs and outputs to the neural network and, hence, reduced the system complexity. As a result, both training requirements and running real time interaction are significantly improved. The expert system would replace and utilise the requirement for skilled dispatchers in scheduling the generators. It is anticipated that this facility is more accurate, dynamic, adaptive and more efficient than a skilled dispatcher. The overall cost of power generation is expected to be less if the new facility is used. Initial results have reflected a satisfactory correlation between predicted and actual results, with a standard deviation error of 1.71% and 1.96% in the base load units of HTPS and ATPS respectively.
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    AI field looks to the future: AAAI ′96, Portland, 4–8 August 1996 (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    URL: http://dx.doi.org/10.1111/j.1468-0394.1996.tb00127.x
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    Increased domain security through application of local security and monitoring (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper presents a model for increasing security within a security domain through the use of localised security services and continuous monitoring. The model divides security services between three logical structures Local Security Units, Local Security Servers and Domain Management Centres. The localisation of security allows the functional divisions within organisations to implement modified security dependent upon their individual needs.
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    ISTAR — a tool for creative design of knowledge bases (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper gives a comprehensive explanation of the Istar knowledge representation software tool. Not only does it describe the features and facilities found in Istar, but it discusses why they are as they are.Istar is one of a new generation of knowledge representation tools, aimed at ill-structured domains of knowledge. While it can be used in traditional KBS projects, in which pieces of knowledge from a domain expert are assembled to form a working knowledge base, it is designed for situations in which there is a large element of creative design: knowledge refinement and generation resulting from the knowledge representation process.The knowledge representation ‘language’ is purely graphical; the knowledge engineer ‘draws’ knowledge on an easel as a box and arrows diagram. Behind this diagram is the knowledge base itself, in the form of integrated inference nets, Bayesian nets and semantic nets. This paper discusses the reasons for these design choices and, briefly, some of the issues faced in development of Istar.
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    A framework for the generation of project-specific quality control for knowledge-based system development (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: : This paper describes a framework for the generation of quality control procedures for knowledge-based system (KBS) projects. KBS projects have their own brand of technical difficulties. These are discussed, and the mismatch between KBS projects and traditional software quality assurance (SQA) approaches is described. An iterative approach to quality is suggested based upon Boehm's Spiral Model of project management. The principles of this approach are described followed by a description of the elements of the framework under development, including inputs, outputs and internal functionality. The operation of the framework is then demonstrated in relation to the Spiral Model. Application of the framework to KBS development project issues is then discussed in relation to current guidelines for KBS quality assurance.
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    Expert system technology in organisational process domain modelling (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Notes: Abstract: Organisational processes are repetitive, time-consuming and interdependent, requiring several members to interact for successful completion. Moreover, when organisations change their operating procedures it becomes difficult to carry out even routine tasks because of the confusion and lack of communication. By studying the organisational processes and the knowledge required to execute them, we can create generic process models that could be stored persistently in a repository. This process repository can serve as a corporate knowledge base, which could be accessed by intelligent computer assistants for automating organisational processes. This paper presents a framework of intelligent assistants that can emulate the behaviour of human agents in organisational problem-solving. The generic process models can also be customised to meet the changing needs of the organisation. We present a domain modelling approach to organisational process modelling and an expert system for customising process models. The paper also describes the architecture and design of the proof-of-concept prototype that supports organisational process modelling, as well as process execution through intelligent computer assistants.
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    News (1996)
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    Call for Papers (1996)
    Oxford, UK : Blackwell Publishing Ltd
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    News (1996)
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    News (1996)
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    Strategies defined for the development of applications using Multilayer Perceptrons: A survey (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Topics: Computer Science
    Notes: Abstract: The success in developing an application employing the Multilayer perceptron (MLP) as knowledge representation form is very dependent on the degree of complexity that the structure of the application's domain has. Different mathematical and/or statistical techniques have been developed to subtract the maximum amount of information of this type from an available sample of the operating space associated to the task of interest. In the context of MLP it has been used to decide on the form the different intervening parameters of the network and/or related learning algorithm (LA) should have. This paper provides an overview of the processes that have been defined to generate network applications using the MLP model, giving particular attention to those based on the dynamic creation of a network's architecture through the application of different techniques for subtracting information about the operating domain in which the training set is subsumed.
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    INVEX: Investment Advisory Expert System (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Capital investment is a very important business decision, because it is largely irreversible and usually long-term. We believe that the use of expert systems as a decision aid for interactive investment decision-making offers several advantages to an unassisted human decision-maker, or even to the human/conventional-DSS combination. For example, the expert system could capture valuable information about so called ‘hard data’, and about the attitude towards some drastic changes in the environment, that are not easy to include in any quantitative method. However, if one expert can play a very important role in the decision-making process, perhaps different experts can be even more valuable, bringing different approaches and somewhat different sets of information to a decision-making situation. Our multiparadigm blackboard framework, called BEST (Blackboard-based Expert Systems Toolkit), allows its user to combine knowledge coming from different experts, and to use different methods/paradigms to capture that knowledge, according to the type of partial problem at hand where each knowledge source is a single paradigm program. In investment decision-making, judgmental investment ranking and selection from expert economists, embedded in a rule-based knowledge source, might be combined with decisions from operational research methods (embedded in a knowledge source that fully respects multicriteria optimization paradigm) and from risk analysis method (embedded in a conventional, procedural knowledge source). When the decisions being combined come from different types of knowledge sources, redundancy is likely to be reduced and the combined decision is likely to be more objective.
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    A knowledge-based framework for intelligent-data migration (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
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    Notes: Abstract: The Object-Inferencing Framework (OIF) is a knowledge-based system developed for intelligent-data migration. The framework provides a mechanism to integrate relational data which represents a source model; a project-specific rulebase which specifies plausible migration scenarios; and a deduction system to facilitate the migration of source data to a new, complex target model. Typically, the target model includes constituents that possess both graphic and tabular components. Although the framework is experimental, industrial applications built upon OIF have been successfully deployed in scenarios in which the source data contained implicit information in that semantic relationships and structure conveyed by the data had to be inferred by a domain expert. This framework provides a substrate for migration from any unstructured or semi-structured data representation to a complex, semantically rich target data model. Examples of the migration of CAD data, which represents an electrical-distribution system, to a client-server based Automated Mapping/Facilities Management (AM/FM) platform are presented to convey the salient features of the design and utility of the OIF. Even though the examples are taken from a specific domain, the approach has potential applications in a myriad of domains, including business enterprises in which the migration of data created and managed by legacy systems to object-oriented and clientserver environments is an area of intense research and development.
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    Book Reviews (1996)
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    Topics: Computer Science
    Notes: A Review of Industrial Case-Based Reasoning Tools Klaus-Dieter Althoff, Eric Auriol, Ralph Barletta and Michel ManagoSmalltalk: An Introduction to Application Development Using Visual Works Trevor Hopkins and Bernard Horan, Prentice HallIntelligent Control in Biomedicine D.A. Linkens (Ed.)Multisensor Integration and Fusion for Intelligent Machines and Systems edited by Ren C. Luo and Michael G. Kay, AblexDelphi Nuts & Bolts for Experienced Programmers G. Cornell and T. Strain
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    Book Reviews (1996)
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    Diary (1996)
    Oxford, UK : Blackwell Publishing Ltd
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    A METHOD FOR COMPUTING ALL MAXIMALLY GENERAL RULES IN ATTRIBUTE-VALUE SYSTEMS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: A method for finding all deterministic and maximally general rules for a target classification is explained in detail and illustrated with examples. Maximally general rules are rules with minimal numbers of conditions. The method has been developed within the context of the rough sets model and is based on the concepts of a decision matrix and a decision function. The problem of finding all the rules is reduced to the problem of computing prime implicants of a group of associated Boolean expressions. The method is particularly applicable to identifying all potentially interesting deterministic rules in a knowledge discovery system but can also be used to produce possible rules or nondeterministic rules with decision probabilities, by adapting the method to the definitions of the variable precision rough sets model.
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    RECURRENT NEURAL NETWORKS AND FINITE AUTOMATA (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: This article studies finite size networks that consist of interconnections of synchronously evolving processors. Each processor updates its state by applying an activation function to a linear combination of the previous states of all units. We prove that any function for which the left and right limits exist and are different can be applied to the neurons to yield a network which is at least as strong computationally as a finite automaton. We conclude that if this is the power required, one may choose any of the aforementioned neurons, according to the hardware available or the learning software preferred for the particular application.
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    CONSTRAINED RESOLUTION AND ABDUCTTVE TEMPORAL REASONING (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: This article presents our work on the effective implementation of abduction in temporal reasoning. This works builds on some results, both in the logic programming field and in the automated reasoning area. We have defined and implemented an abductive procedure, which is well adapted for temporal reasoning because it is based on a constrained resolution principle. Constrained resolution has two advantages for temporal reasoning: First, it allows us to deal efficiently with temporal ordering and equality predicates, which are otherwise too much trouble with classical resolution; second, it allows a restricted form of abduction where hypotheses are limited to ordering relationships. From the logic programming area, our work uses results and procedures developed by others in the abductive logic programming field. The procedure we define and implement in this work is relatively independent of the temporal formalism: It has been used with some reified temporal logics and with the event calculus. More generally it can be used on any point-based temporal formalism, provided that a correct and complete algorithm is available for checking the consistency of a set of temporal ordering relationships in this language.
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    ON THE IMPLEMENTATION AND EVALUATION OF AbTweak (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: In this paper, we describe the implementation and evaluation of the AbTweak planning system, a test bed for studying and teaching concepts in partial-order planning, abstraction, and search control. We start by extending the hierarchical, precondition-elimination abstraction of ABSTRIPS to partial-order-based, least-commitment planners such as Tweak. The resulting system, AbTweak, illustrates the advantages of using abstraction to improve the efficiency of search. We show that by protecting a subset of abstract conditions achieved so far, and by imposing a bias on search toward deeper levels in a hierarchy, planning efficiency can be greatly improved. Finally, we relate AbTweak to other planning systems SNLP, ALPINE, and SIPE by exploring their similarities and differences.
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    PATTERN-BASED LEARNING AND SPATIALLY ORIENTED CONCEPT FORMATION IN A MULTI-AGENT, DECISION-MAKING EXPERT (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: As they gain expertise in problem solving, people increasingly rely on patterns and spatially oriented reasoning. This paper describes an associative visual-pattern classifier and the automated acquisition of new, spatially oriented reasoning agents that simulate such behavior. They are incorporated into a multi-agent game-learning program whose architecture robustly combines agents with conflicting perspectives. When tested on three games, the visual-pattern classifier learns meaningful patterns, and the pattern-based, spatially oriented agents generalized from these patterns are generally correct. The accuracy of the contribution of each of the newly created agents to the decision-making process is measured against an expert opponent, and a perceptron-Iike algorithm is used to learn game-specific weights for these agents. Much of the knowledge encapsulated by the new agents was previously inexpressible in the program's representation and in some cases is not readily deducible from the rules.
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    TEMPORAL REASONING WITH THE MODAL LOGIC Z (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: This article presents a formal theory of concurrent actions that handles the qualification, ramification, and frame problems. The theory is capable of temporal explanation, i.e., reasoning forward and backward. The approach uses the modal logic Z to extend the work of Lifschitz and Rabinov on miracle-based temporal reasoning. The advantages of miracles for describing unknown actions are augmented with the ability to handle concurrent actions that can provide for the most economical explanation of state changes. For temporal explanation problems restricted to finite domains, it has a worst-case exponential decision procedure. The theory is as general as first-order logic in what it can express as preconditions and consequences of actions.
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    HYPOTHETICAL REASONING ABOUT ACTIONS: FROM SITUATION CALCULUS TO EVENT CALCULUS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    Notes: Hypothetical reasoning about actions is the activity of preevaluating the effect of performing actions in a changing domain; this reasoning underlies applications of knowledge representation, such as planning and explanation generation. Action effects are often specified in the language of situation calculus, introduced by McCarthy and Hayes in 1969. More recently, the event calculus has been defined to describe actual actions, i.e., those that have occurred in the past, and their effects on the domain. Altough the two formalisms share the basic ontology of atomic actions and fluents, situation calculus cannot represent actual actions while event calculus cannot represent hypotethical actions. In this article, the language and the axioms of event calculus are extended to allow representing and reasoning about hypothetical actions, performed either at the present time or in the past, altough counterfactuals are not supported. Both event calculus and its extension are defined as logic programs so that theories are readily adaptable for Prolog query interpretation. For a reasonably large class of theories and queries, Prolog interpretation is shown to be sound and complete w.r.t. the main semantics for logic programs.
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    IT'S ABOUT TIME: AN INTRODUCTION TO THE SPECIAL ISSUE ON TEMPORAL REPRESENTATION AND REASONING (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00266.x
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    LEARNING MONOTONIC-CONCAVE INTERVAL CONCEPTS USING THE BACK-PROPAGATION NEURAL NETWORKS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Monotonicity and concavity play important roles in human cognition, reasoning, and decision making. This paper shows that neural networks can learn monotonic-concave interval concepts based on real-world data, Traditionally, the training of neural networks has been based only on raw data. In cases where the training samples carry statistical fluctuations, the products of the training have often suffered. This paper suggests that global knowledge about monotonicity and concavity of a problem domain can be incorporated in neural network training. This paper proposes a learning scheme for the back-propagation layered neural networks in learning monotonic-concave interval concepts and provides an example to show its application.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00262.x
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    INTRODUCTION TO THE SPECIAL ISSUE ON GAMES: STRUCTURE AND LEARNING (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
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    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00249.x
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    A STRENGTHENED ALGORITHM FOR TEMPORAL REASONING ABOUT PLANS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Allen's interval algebra has been shown to be useful for representing plans. We present a strengthened algorithm for temporal reasoning about plans, which improves on straightforward applications of the existing reasoning algorithms for the algebra. This is made possible by viewing plans as both temporal networks and hierarchical structures. The temporal network view allows us to check for inconsistencies as well as propagate the effects of new temporal constraints, whereas the hierarchical view helps us to get the strengthened results by taking into account the dependency relationships between actions.We further apply our algorithm to the process of plan recognition through the analysis of natural language input. We show that such an application has two useful effects: the temporal relations derived from the natural language input can be used as constraints to reduce the number of candidate plans, and the derived constraints can be made more specific by combining them with the prestored constraints in the plans being recognized.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00265.x
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    KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00252.x
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    LEARNING OF RESOURCE ALLOCATION STRATEGIES FOR GAME PLAYING (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Human chess players exhibit a large variation in the amount of time they allocate for each move. Yet, the problem of devising resource allocation strategies for game playing has not received enough attention. In this paper we present a framework for studying resource allocation strategies. We define allocation strategy and identify three major types of strategies: static, semi-dynamic, and dynamic. We then describe a method for learning semi-dynamic strategies from self-generated examples. We present an algorithm for assigning classes to the examples based on the utility of investing extra resources. The method was implemented in the domain of checkers, and experimental results show that it is able to learn strategies that improve game-playing performance.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00254.x
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    LEARNING PLAYING STRATEGIES IN CHESS (1996)
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: It is believed that chess masters use pattern-based knowledge to analyze a position, followed by a pattern-based controlled search to verify or correct the analysis. This paper describes a first-order system called PAL that can learn patterns in the form of Horn clauses from simple example descriptions and general purpose knowledge. It is shown how PAL can leam chess patterns that are beyond the learning capabilities of current inductive systems. The patterns learned by PAL can be used for analysis of positions and for the construction of playing strategies. By taking the learned patterns as attributes for describing examples, a set of rules which decide whether a Pawn can safely be promoted without moving the King in a King and Pawn vs King endgame, is automatically constructed with a similarity-based learning algorithm. Similarly, a playing strategy for the King and Rook vs King endgame is automatically constructed with a simple learning algorithm by following traces of games and using the patterns learned by PAL. Limitations of first-order systems, PAL imparticularly, are exposed in domains where a large number of background definitions may be required for induction. Conclusions and future research directions are given.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1467-8640.1996.tb00253.x
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  • 86
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    Reimbursements up, coding time down (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00273.x
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    Call for Papers (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00278.x
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    Negotiation in a knowledge-based concurrent engineering design environment (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Computational support for concurrent engineering design presents a number of issues in the design of knowledge-based systems. A fundamental concern is the need to provide the life-cycle perspective in recommending design alternatives. It is argued that such a complex knowledge-based system should be distributed, due to the inherent problems with large knowledge bases and the maintenance of consistency. Inconsistent local views of a problem and different priorities on design issues are expected between different knowledge-based design perspectives. These inconsistencies and different priorities will lead inherently to conflict which has to be resolved. This paper addresses the issues and key variables in conflict resolution and presents a strategy that can be applied for managing the conflict resolution process. We propose negotiation as the method of analysing a conflict situation, applying an appropriate conflict resolution strategy and monitoring its performance. We present an overview of the nature of conflict and some conflict resolution strategies, and see in what situations certain strategies are appropriate.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00046.x
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    Computers learn to smell and taste (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: They all stink: food and drink, perfumery, household products, soaps, shampoos, paints, manufacturing processes, printing processes, waste products, contaminated air, and automotive emissions and environmental testing. In every case, small is a criterion of quality.Automated techniques to ‘smell’ or ‘taste’ liquids using mass spectrometry and gas chromatography are time consuming, require skilled personnel and often do not give the information required for qualitative ‘testing’. A new technique is now available due to the advances in neural computing technology and multi-sensor array technology. The combination of these two approaches tries to simulate the human olfactory system in a simplified form. This paper shows that the recognition ability of an odour sensor array will be significantly improved using a neural computing approach in order to discriminate between similar odours.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00048.x
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    Applications (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00051.x
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    Languages (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00059.x
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    Tools (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00058.x
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    Designing for flexibility: a case study (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Expert systems have traditionally been designed with one particular purpose in mind, whether problem-solving, critiquing etc. When the system is intended for users with varying background knowledge it becomes necessary to provide different facilities for different groups of users, which in turn puts demands on how the knowledge must be represented. This paper describes an industrial prototype—Protein Purification Advisor (PPA)—in the area of protein purification, and how a suitable choice of knowledge representation has allowed us to use the same knowledge for a number of purposes including those mentioned above. Particular interest is laid on the topic of how to represent the heuristic knowledge and how to use it in actual decision-making.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00023.x
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    Knowledge acquisition and adaptation: a genetic approach (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: A genetic algorithm-based (GA-based) system (GAPOLE) is used to evolve a self-learning, self-optimising control strategy for a typical inherently unstable, dynamic system—a simulated pole-cart system. The dynamics of the system are unknown to GAPOLE. The only information for evaluating performance is a signal indicating that the pole-cart system is out of control. This presents a genuinely difficult credit assignment problem. We present some evidence which shows that GAPOLE compares well with the best alternative methods, but it is noteworthy that it is most robust. It is argued that maintaining a population of partial solutions offers some advantages: GA-based algorithms can deliver more than one good solution at a time; they are able to adapt better in complex changing conditions. Results characterising the performance of the method as population size is varied are also presented. The results show that GAPOLE performed best with a population size of 300. Therefore it is suggested that this parameter, like other GA parameters, may have to be tailored to a particular application. This appears to contradict an earlier claim that a population size in the range of 60–110 is optimal for genetic algorithm-based applications (Grefenstette 1986) across domains.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00021.x
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    Intelligent agents (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00032.x
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    Languages (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00036.x
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    Fuzzy logic (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00040.x
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    Countermatch in the community (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00050.x
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    Neural networks (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00053.x
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    Virtual reality tools (1995)
    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.1995.tb00057.x
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