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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 2
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The Allen and Koomen planner is intractable in two ways: the Allen interval algebra is an intractable temporal reasoner, and the collapsing problem introduces a large branching factor in the search space for a solution plan. We define independence and dependence for networks to address both problems. Independence is used to find a decomposition of an interval network, and dependence is used to focus search when faced with the collapsing problem.
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  • 3
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We analyze the problem of computing the minimal labels for a network of temporal relations in point algebra. Van Beek proposes an algorithm for accomplishing this task, which takes O(max(n3, n2 m)) time (for n points and m ≠-relations). We show that the proof of the correctness of this algorithm given by van Beek and Cohen is faulty, and we provide a new proof showing that the algorithm is indeed correct.
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  • 4
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: As influence diagrams become a popular representational tool for decision analysis, influence diagram evaluation attracts more and more research interests. In this article, we present a new, two-phase method for influence diagram evaluation. In our method, an influence diagram is first mapped onto a decision graph and then the analysis is carried out by evaluating the decision graph. Our method is more efficient than Howard and Matheson's because, among other reasons, our method generates a much smaller decision graph for the same influence diagram. Like those most recent algorithms reported in the literature, our method also provides a clean interface between influence diagram evaluation and Bayesian net evaluation. Consequently, various well-established algorithms for Bayesian net evaluation can be used in influence diagram evaluation. Furthermore, our method has a few unique merits. First, it takes advantage of asymmetry in influence diagrams to avoid unnecessary computation. Second, by using heuristic search techniques, it provides an explicit mechanism for using heuristic information that may be available in a domain-specific form. These additional merits make our method more efficient than the current algorithms in general. Finally, by using decision graphs as an intermediate representation, the value of perfect information can be computed in a more efficient way.
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  • 5
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Vagueness and uncertainty have attracted the attention of philosophers and logicians for many years. Recently, AI researchers contributed essentially to this area of research. Fuzzy set theory and the theory of evidence are seemingly the most appealing topics. On this note we present a new approach, based on the rough set theory, for looking to these problems. The theory of rough sets seems a suitable mathematical tool for dealing with problems of vagueness and uncertainty. This paper is a modified version of the author's lecture titled “An inquiry into vagueness and uncertainty,” which was delivered at the AI Conference in Wigry (Poland), 1994.
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  • 6
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper presents results of experiments showing how machine learning methods arc useful for rule induction in the process of knowledge acquisition for expert systems. Four machine learning methods were used: ID3, ID3 with dropping conditions, and two options of the system LERS (Learning from Examples based on Rough Sets): LEM1 and LEM2. Two knowledge acquisition options of LERS were used as well. All six methods were used for rule induction from six real-life data sets. The main objective was to lest how an expert system, supplied with these rule sets, performs without information on a few attributes. Thus an expert system attempts to classify examples with all missing values of some attributes. As a result of experiments, it is clear that all machine learning methods performed much worse than knowledge acquisition options of LERS. Thus, machine learning methods used for knowledge acquisition should be replaced by other methods of rule induction that will generate complete sets of rules. Knowledge acquisition options of LERS are examples of such appropriate ways of inducing rules for building knowledge bases.
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  • 7
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Knowledge discovery in databases, or dala mining, is an important direction in the development of data and knowledge-based systems. Because of the huge amount of data stored in large numbers of existing databases, and because the amount of data generated in electronic forms is growing rapidly, it is necessary to develop efficient methods to extract knowledge from databases. An attribute-oriented rough set approach has been developed for knowledge discovery in databases. The method integrates machine-learning paradigm, especially learning-from-examples techniques, with rough set techniques. An attribute-oriented concept tree ascension technique is first applied in generalization, which substantially reduces the computational complexity of database learning processes. Then the cause-effect relationship among the attributes in the database is analyzed using rough set techniques, and the unimportant or irrelevant attributes are eliminated. Thus concise and strong rules with little or no redundant information can be learned efficiently. Our study shows that attribute-oriented induction combined with rough set theory provide an efficient and effective mechanism for knowledge discovery in database systems.
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  • 8
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper presents an empirical study of the use of the rough set approach to reduction of data for a neural network classifying objects described by quantitative and qualitative attributes. Two kinds of reduction are considered: reduction of the set of attributes and reduction of the domains of attributes. Computational tests were performed with five data sets having different character, for original and two reduced representations of data. The learning time acceleration due to data reduction is up to 4.72 times. The resulting increase of misclassification error does not exceed 11.06%. These promising results let us claim that the rough set approach is a useful tool for preprocessing of data for neural networks.
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  • 9
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In this paper, we introduce the notion of interval structures in an attempt to establish a unified framework for representing uncertain information. Two views are suggested for the interpretation of an interval structure. A typical example using the compatibility view is the rough set model in which the lower and upper approximations form an interval structure. Incidence calculus adopts the allocation view in which an interval structure is defined by the tightest lower and upper incidence bounds. The relationship between interval structures and interval-based numeric belief and plausibility functions is also examined. As an application of the proposed model, an algorithm is developed for computing the tightest incidence bounds.
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  • 10
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: “Simpson's paradox,” first described nearly a century ago, is an anomaly that sometimes arises from pooling data. Dramatic instances of the paradox have occurred in real life in the domains of epidemiology and admissions policies. Many writers have recently described hypothetical examples of the paradox arising in other areas of life and it seems possible that the paradox may occur frequently in mundane domains but with less serious implications. Thus, it is not surprising that the paradox should arise in commonsense reasoning, that subarea of artificial intelligence that seeks to axiomatize reasoning in such mundane domains. It arises as the problem “approximate proof by cases” and the question of whether to accept it may well depend on whether we wish to construct performance or competence models of reasoning. This article gives a brief history of the paradox and discusses its occurrence in our own discipline. It argues that if the paradox occurs frequently but undramatically in real life, every uncertain reasoning system will have to deal with the problem in some way.
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  • 11
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We present the syntax and proof theory of a logic of argumentation, LA. We also outline the development of a category theoretic semantics for LA. LA is the core of a proof theoretic model for reasoning under uncertainty. In this logic, propositions are labeled with a representation of the arguments which support their validity. Arguments may then be aggregated to collect more information about the potential validity of the propositions of interest. We make the notion of aggregation primitive to the logic, and then define strength mappings from sets of arguments to one of a number of possible dictionaries. This provides a uniform framework which incorporates a number of numerical and symbolic techniques for assigning subjective confidences to propositions on the basis of their supporting arguments. These aggregation techniques are also described with examples.
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  • 12
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In this paper we focus on the temporal constraints between causes and effects of causal relations, and, to deal correctly with such relations, we stress the importance of analyzing the action-types (aspectual category) of causes and effects. In particular, we propose a domain-independent ontology in which the distinctions between action-types (e.g., the distinction between durative and punctual situations) are dealt with, and different types of causal relations are distinguished, on the basis of (i) the temporal constraints they impose between causes and effects (these constraints are expressed in a temporal formalism that extends Vilain's point interval algebra) and (ii) the action-types of their causes and effects. Our ontology allows one to capture precisely the temporal constraints imposed by causation and the action-types of the related situations. Moreover, in case the user has no accurate knowledge about the action-types of some situations and/or the types of some causal connections to be dealt with, our formalism allows the user to leave the descriptions underspecified, and more specific pieces of information may be inferred. Inferences provide a flow of information about action-types to information about temporal constraints in causation and vice versa, and demonstrate that a deep integration of time and causation is provided also at the inferential level.
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  • 13
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The Galois (or concept) lattice produced from a binary relation has proved useful for many applications. Building the Galois lattice can be considered a conceptual clustering method because it results in a concept hierarchy. This article presents incremental algorithms for updating the Galois lattice and corresponding graph, resulting in an incremental concept formation method. Different strategies are considered based on a characterization of the modifications implied by such an update. Results of empirical tests are given in order to compare the performance of the incremental algorithms to three other batch algorithms. Surprisingly, when the total time for incremental generation is used, the simplest and less efficient variant of the incremental algorithms outperforms the batch algorithms in most cases. When only the incremental update time is used, the incremental algorithm outperforms all the batch algorithms. Empirical evidence shows that, on the average, the incremental update is done in time proportional to the number of instances previously treated. Although the worst case is exponential, when there is a fixed upper bound on the number of features related to an instance, which is usually the case in practical applications, the worst-case analysis of the algorithm also shows linear growth with respect to the number of instances.
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  • 14
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    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We propose a procedure for estimating DBLEARN's potential for knowledge discovery, given a relational database and concept hierarchies. This procedure is most useful for evaluating alternative concept hierarchies for the same database. The DBLEARN knowledge discovery program uses an attribute-oriented inductive-inference method to discover potentially significant high-level relationships in a database. A concept forest, with at most one concept hierarchy for each attribute, defines the possible generalizations that DBLEARN can make for a database. The potential for discovery in a database is estimated by examining the complexity of the corresponding concept forest. Two heuristic measures are defined based on the number, depth, and height of the interior nodes. Higher values for these measures indicate more complex concept forests and arguably more potential for discovery. Experimental results using a variety of concept forests and four commercial databases show that in practice both measures permit quite reliable decisions to be made; thus, the simplest may be most appropriate.
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  • 15
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The inverted pendulum poses serious problems for qualitative modeling methods, so it is a good benchmark to lest their performance. This paper shows how a new data analysis method known as rough set theory can be utilized to swing up and stabilize the pendulum. Our approach to this task consists of deriving control rules from the actions of a human operator stabilizing the pendulum and subsequently using them for automatic control. Rule derivation is based on the “learning from examples” principle and does not require knowledge of a quantitative model of the system.
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  • 16
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    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We present some methods, based on the rough set and Boolean reasoning approaches, for extracting laws from decision tables. First we discuss several procedures for decision rules synthesis from decision tables. Next we show how to apply some near-to-functional relations between data to data filtration. Two methods of searching for new classifiers (features) are described: searching for new classifiers in a given set of logical formulas, and searching for some functions approximating near-to-functional relations.
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  • 17
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    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We apply rough set constructs to inductive learning from a database. A design guideline is suggested, which provides users the option to choose appropriate attributes, for the construction of data classification rules. Error probabilities for the resultant rule are derived. A classification rule can be further generalized using concept hierarchies. The condition for preventing overgeneralization is derived. Moreover, given a constraint, an algorithm for generating a rule with minimal error probability is proposed.
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  • 18
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Increased interest in problem-solving decisions in the area of engineering leads to an increased demand for expert system applications. This paper presents an expert system that detects faults in hydraulic systems by simulating the reasoning of the expert, using as guide the hydraulic circuit of the system on the screen and extensive graphical information. A graphical user interface, appropriate explanations by using hypertext and user modelling have been implemented in order to produce a system that overcomes the usual interface problems of expert systems in engineering. This system has been developed in close collaboration with the company Automation Systems SA (Mannesmann Rexroth — Greece) and is currently used to detect faults in hydraulic presses, a fact that presents evidence of its usefulness.
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  • 19
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Retrieving ad hoc data from information systems is difficult for non-expert users. Despite the efforts made in improving query tools (e.g. visual query construction, Query By Example, query templates), empirical research shows that constructing a request is still difficult (Reisner 1988). The core of the problem seems to be in the difference between the way the user perceives the application domain and the way the system requires the user to see it (Carroll & Olsen 1988). In this paper we describe the design and implementation of an ad hoc query tool developed by RCC for a personnel information system, and how AI techniques contributed to this module. The main novel idea incorporated in the query tool is to present the user with a means to question the conceptual model of the system instead of the technical model. To support this, a blackboard architecture has been designed and implemented with knowledge sources that translate the user's questions to database queries. The query tool is used in daily practice by over 100 users.
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  • 21
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: A fuzzy reasoning algorithm is presented in this paper. It is based on the concept of a generalised fuzzy production rule that adds new conjunctions such as ADD and REL to the usual AND and OR conjunctions for the linkage of premises in conventional rules. A definition is given for weights and related factors, to express and measure a relation between the premises. A formal representation for fuzzy premises is presented, together with the introduction of a fuzzy match method. Multiple thresholds are used to convert the uncertainty measures of reasoning results into linguistic variables. We have applied the fuzzy reasoning algorithm to a frame-based hybrid expert system tool. An object-oriented approach is used in implementing the system. Some results of the application are presented and discussed.
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  • 22
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Architectural design is a complex task which requires expert knowledge, a great deal of experience and no small amount of creativity and artistic flair. However, while humans are very good at creativity, intuition, artistry and evaluation, they are notoriously bad at routine mundane tasks. Searching through large databases of past designs can be such a task. This can result in useful design knowledge being ignored. In this paper we present a way to aid architects in their work by providing a software tool aimed at recording, retrieving and evaluating architectural designs.
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  • 23
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The purpose of this research is to present a comprehensive bibliography of neural network application research in business. One hundred and twenty-seven neural network application papers and reports are identified through exhaustive literature searches. A classification of these articles by application area reveals that neural networks are being used for a diverse range of corporate functional activities, particularly in the areas of production/operations and finance. Information on the neural network development language/tool, the learning paradigm and the computer operating environment as reported in each article is included. Those journals which have published the most neural network business applications are also presented.
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  • 24
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: A real-time visual servo tracking system for an industrial robot has been developed. Instead of a charge coupled device (CCD), a position sensitive detector (PSD) is used as the real-time vision sensor due to its fast response (the light position is transduced to analogue current). A neural network learns the complex association between the 3D object position and its sensor reading, and uses it to track that object, either moving or stationary. It also turns out that this scheme lends itself to a user-friendly way to teach workpaths for industrial robots. Furthermore, for real-time use of the neural net, an efficient neural network architecture has been developed based on the concept of input space partitioning and local learning. Real experiments indicate the system's characteristics of fast processing and learning as well as optimal usage of network resources.
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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    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.
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  • 26
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    Expert systems 12 (1995), S. 0 
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  • 27
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    Expert systems 12 (1995), S. 0 
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    Expert systems 12 (1995), S. 0 
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    Topics: Computer Science
    Notes: Abstract: Research into the development and impacts of expert systems has accumulated to a point where it may be said to constitute a distinct field of study. As such, the evolution, organisation and dissemination of expert system research are themselves topics for investigation. Here we focus on the dissemination aspect, providing objective rankings of journals that have had the greatest impacts on recent expert system research. Our study examines the citation patterns of all research published in five expert systems journals during the past five years. Over 14 000 citations to more than 800 journals are analysed under two kinds of ranking schemes. These are based on cumulative citation counts and normalised citation counts. The latter adjusts for the number of years a journal article has been available to be cited. The reported rankings will be of interest to all who want to know where scientific developments that influence expert system research are reported: those who conduct, support, evaluate and study expert system research.
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
    Notes: Abstract: In this paper we describe TheMD (The Methods Designer) shell and its use in the development of an expert system, known as Dust-Expert, for the relief of dust explosions. We begin by providing the motivation for the development of TheMD Shell by evaluating a prototype implementation of Dust-Expert using a conventional shell. This evaluation is carried out in terms of the transparency, reliability and extensibility of the system.The lessons learned from this evaluation have led to the development of TheMD Shell. We describe the main features of the shell which include more appropriate schemas, more complete explanation capabilities, a ranking scheme and equation-solving capabilities. We illustrate the use of the schemas and the importance of the equation-solving capabilities by examples from the domain of dust explosions. We also provide a formal specification of the ranking scheme that we adopt. We conclude by highlighting the benefits of our approach in comparison to the usual process of developing knowledge-based systems.
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
    Notes: Subjective Probability George Wright and Peter Ayton (Eds.)Knowledge-based Information Systems D. Partridge and K. M. HussainIntelligent Agents: the New Revolution in Software Christine Guilfoyle and Ellie WarnerHigh Performance Computing Demystified D. Loshin, AP ProfessionalKnowledge Processing and Applied Artificial Intelligence Soumitra Dutta
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    Notes: Abstract: A knowledge-based system (KBS) could be an ideal decision tool to reduce the complexity of planning non-destructive evaluation (NDE) or scheduling inspections. Such a KBS would have to evaluate the advantages and limitations of each available technique, given the specificity of a problem, and incorporate the fundamental knowledge derived from failure analysis. The KBS should include topics such as materials vs. defect size and type, probability of failure, and basic reliability information. In order to organise knowledge of materials degradation efficiently, the parameters that control various forms of failure first have to be rationalised in a general framework. This framework and their factors would then constitute a quantitative and easily programmable description of the independent variables controlling the intensity of a failure. This paper describes such a framework which could guide the general selection of NDE for materials failure, with a particular emphasis on corrosion related failures. The framework architecture itself was constructed using an object-oriented methodology for maximum flexibility, since it was anticipated that the materials parameters could easily be described as multidimensional objects.
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    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.
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    Notes: Abstract: This paper presents a knowledge-based system for task allocation in a network of processors. Since the problem is NP-complete, optimisation techniques are computationally prohibitive and impractical. Our approach reduces computational burden by using (1) a two-level hierarchical scheduling model to alleviate the problem complexity, and (2) a search strategy that uses knowledge from the knowledge base to limit the search space to a manageable size. The major goal of our approach is to generate good but not necessarily optimal solutions quickly. The system is implemented on a Sun SPARCstation 1 + using Common Lisp. Our computational experience in using this system for task allocation indicates that the two-level hierarchical approach generates better schedules in shorter computational time than a non-hierarchical approach.
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    Notes: Abstract: This paper proposes a fuzzy post adjustment (FPA) mechanism so that human knowledge and machine knowledge can be integrated more synergistically to improve the performance of expert systems. Machine knowledge means knowledge algorithmically derived from past instances. Human knowledge implies (1) expert knowledge judging the trends of external factors and (2) user knowledge representing users’personal views about information given by both expert knowledge and machine knowledge. We consider an expert system that uses the FPA mechanism to incorporate the effect of external factors effectively into its inference process. The goal of this expert system is stock market timing prediction, which is divided into four kinds: bull, edged-up, edged-down and bear. Empirical tests showed that the proposed FPA mechanism can improve the performance of an expert system significantly, even in a turbulent decision-making environment.
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    Notes: Abstract: There is still a need for new knowledge elicitation techniques and tools. Laddering is a technique which has a long history in a wide range of disciplines and which has proved extremely useful in knowledge elicitation. There have, however, been few attempts to describe and survey the technique per se. This paper describes the technique, its background, its use, analysis, and automation, with particular reference to knowledge elicitation. The advantages and disadvantages of the technique are described. It is concluded that laddering is a valuable technique which could be used in a wide range of settings.
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    Notes: The Art and Science of Smalltalk: An Introduction to Object Oriented Programming Using VisualWorks Simon LewisThe Book of GENESIS: Exploring Realistic Neural Models with the General Neural Simulation System James Bower and D. BeemanThe Book of GENESIS: Exploring Real istic Neural Models with the General Neural Simulation System James Bower and D. BeemanThe ISDN Literacy Book Gerald L. HopkinsThe Virtual Reality Casebook Carl Eugene LoeHer and Tim
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    Notes: Abstract: The design of telecommunication networks is a complex activity involving a vast amount of input data and numerous design rules. Much of the data is estimated and many of the rules are based upon experiential knowledge. The use of existing uncertainty techniques in expert systems is not really suited to the complexity of telecommunication network design. Having investigated the uncertainty problem, it is believed that a more rational method has been found for use in this application area. The paper presents the ‘Uncertainty Window’technique and its testing on one aspect of network design, namely that of network synchronisation.The essence of this uncertainty process is one of associating individual uncertainty windows with the relevant rules, data and facts of a design problem, which results in providing the network designer with an insight into the possible uncertainties within a design at each stage of the process. It indicates which information sources provide the dominant uncertainty and which assumptions are critical, needing further investigation, in order to improve the level of confidence in the overall design. The windowing technique works by virtue of its ability to retain the composition of the uncertainties within the problem and their associated values, assumptions, and so forth and allows for better solutions to be obtained.
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    Notes: Abstract: Prolog/Rex supports the construction of knowledge-based systems, allowing frames (Prolog/Rex concepts) and rules to be combined, and providing language level support for hypothetical reasoning and assumption-based truth maintenance (Prolog/Rex viewpoint mechanism). To increase run-time performance during rule execution, Prolog/Rex provides two complementary rule compilation techniques: the simple indexing scheme and the heavily modified Rete expansion method. To improve the efficiency of the inference engine, we built an agenda-based rule manager that uses priority mechanism and/or heuristics embedded in meta-rules to control the rule firing order. Forward- and backward-chaining can be combined within the same program.
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    Notes: Abstract: Process supervision consists of following the temporal evolution (change) of process behaviours. This task has usually been performed based on the knowledge and experience of domain experts and operators. Actually, these experts and operators almost always express their experience and knowledge about process evolution in an imprecise, fuzzy and vague way. A good supervision system should be capable of dealing at once with two different kinds of knowledge: time and uncertainty.For many years, time and uncertainty have been two of the most important topics in Artificial Intelligence research and applications. Many approaches have been proposed to deal with either one or the other. Among the various approaches for time, reified logic has been considered as the most influent one. Possibilistic logic, on the other hand, has shown its ability to handle uncertain knowledge and information. This paper describes an approach for managing temporal uncertainty based on fuzzy logic and possibility theory. A fuzzy temporal expert system shell has been developed to perform process supervision tasks.
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    Notes: Abstract: During the last decade, cumulative trauma disorders have become a major concern both to occupational health and safety professionals and manufacturing industries. This paper will present the development of a knowledge-based system for predicting the potential of developing strain injuries among employees exposed to repetitive and forceful activities. This potential is identified through the use of an expert system incorporating a fuzzy set algorithm. Recommendations for the prevention of the resulting CTDs are then provided by the system. The system executes on a microcomputer platform, and was constructed utilising a commercial object-oriented expert system shell.
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    Notes: Abstract: The recent surge of interest in connectionist models arose through the availability of high speed parallel supercomputers and the advent of new learning algorithms. The computations performed on concurrent architectures are less costly than similar ones performed on sequential machines. In this paper, the design and implementation of a parallel version of fuzzy ARTMAP (Carpenter et al. 1992), which encompasses both neural and fuzzy logic, is discussed. Fuzzy ARTMAP is a supervised learning algorithm utilising two fuzzy ART modules and an associated mapping network. A simplified version of fuzzy ARTMAP (SFAM) was designed by incorporating a simplification of the match tracking concept on unsupervised fuzzy ART paradigms. The proposed simplified version consists of only one fuzzy ART module and an associated mapping network. A parallel fuzzy ARTMAP (PFAM) algorithm is then designed and implemented on a hypercube simulator (iPSC). The algorithm is parallelised for any architecture and, with the exception of issues related to communications, the implementation remains the same on any type of parallel machine. PFAM enjoys the advantage of reduced training time that makes the algorithm a successful candidate for applications that require both online testing and training. Such applications can range from underwater sonar detection and chemical plant processing control to nuclear reactor process control, flexible manufacturing and systems analysis.
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    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.
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    Notes: Abstract: The KADS methodology (Schreiber et al. 1993; Tansley & Hayball 1993) and its successor, CommonKADS (Wielinga et al. 1992) have proved to be very useful approaches for modelling the various transformations involved between eliciting knowledge from an expert and encoding this knowledge in a computer program. These transformations are represented in a series of models. While it is widely agreed that these methods are excellent approaches from a theoretical viewpoint, the documentation provided concentrates on defining what models should be produced, with only general guidance on how the models should be produced. This has the advantage of making KADS and CommonKADS widely applicable, but it also means that considerable training and experience is required to become proficient in them. This paper reviews three projects that investigated the feasibility of producing specific guidance for certain decisions which are required when using KADS or CommonKADS to develop a knowledge-based system. Guidance was produced for the identification of the generic task addressed by a knowledge-based system; for the selection of appropriate AI techniques for implementing the analysed knowledge; and for selecting a suitable tool for implementing the system. Each set of guidance was encoded in its own knowledge-based system, which was itself developed with the assistance of KADS or CommonKADS. These projects therefore both studied and applied KADS and CommonKADS in order to produce knowledge-based guidance for knowledge engineers. The projects showed that it was feasible to produce heuristic guidance which could be understood, applied and occasionally overridden by knowledge engineers. The guidance provides reasonably experienced knowledge engineers with a framework for making the key decisions required by CommonKADS, in the same way that CommonKADS provides knowledge engineers with a framework for representing knowledge. The projects also produced some new insights about CommonKADS domain modelling and about the process of task identification.
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    Notes: Control strategies that decompose the competence of an agent into independent, task-achieving control structures are emerging as viable alternatives to the notion that a robot is an explicit symbol processing device with input and output extensions in the form of sensors and actuators. This approach draws inspiration from ethology and the cognitive sciences, where the competence of biological creatures is seen to be a result of the successful combination of several distinct behavior patterns that enable them to interact effectively with their environments.The distinction between classical approaches that view intelligent behavior as the outcome of symbolic manipulations and an alternate approach that asserts that it is the careful integration of distributed, goal-competent control structures that lead to intelligent behavior is analyzed in detail. It is found that this dichotomy can be said to arise from the paradigm that is chosen to represent the knowledge at the disposal of the agent. Structurally encoded knowledge requiring an active interpreter for the knowledge to be exhibited in action leads to the symbol processing paradigm for intelligent behavior, whereas the interactive model for knowledge representation assumes that the knowledge at the disposal of an active agent resides within goal-competent, interactive control structures.A formalism is developed for representing the goal-directed nature of these interactive control structures with clear control-module boundaries. An implementation is then presented to demonstrate some of the basic features of this methodology.
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    Notes: We have previously reported a number of tractable planning problems defined in the SAS+ formalism. This article complements these results by providing a complete map over the complexity of SAS+ planning under all combinations of the previously considered restrictions. We analyze the complexity of both finding a minimal plan and finding any plan. In contrast to other complexity surveys of planning, we study not only the complexity of the decision problems but also the complexity of the generation problems. We prove that the SAS+-PUS problem is the maximal tractable problem under the restrictions we have considered if we want to generate minimal plans. If we are satisfied with any plan, then we can generalize further to the SAS+-US problem, which we prove to be the maximal tractable problem in this case.
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    Notes: Sentential theories of belief hold that propositions (the things that agents believe and know) are sentences of a representation language. To analyze quantification into the scope of attitudes, these theories require a naming map a function that maps objects to their names in the representation language. Epistemic logics based on sentential theories usually assume a single naming map, which is built into the logic. I argue that to describe everyday knowledge, the user of the logic must be able to define new naming maps for particular problems. Since the range of a naming map is usually an infinite set of names, defining a map requires quantification over names. This paper describes an epistemic logic with quantification over names, presents a theorem-proving algorithm based on translation to first-order logic, and proves soundness and completeness. The first version of the logic suffers from the problem of logical omniscience; a second version avoids this problem, and soundness and completeness are proved for this version also.
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    Notes: This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain.There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.
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    Notes: In order to provide a background for rough set modeling of uncertainty, two types of incompleteness of information are discussed. Representation of uncertain knowledge acquired from incomplete information is outlined within the framework of information logics. Relational proof theory for the information logics is presented. It is shown how these logics and their proof systems can be handled in the GLEFATINF (Graphical & Logical Editing Framework) system. This computer program is a key component of the inference laboratory Atelier d'Inféence (ATINF) developed at LIFIA-IMAG, our lab. It provides a general framework, independent of logic and proof systems, for combining inference tools, editing, and checking proofs. The basic principles of its design and implementation are given and its capabilities are discussed. Its application to define the information logics and their proof systems and to present proofs in these proof systems is discussed and illustrated.
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    Notes: One of the most important problems in the application of knowledge discovery systems is the identification and subsequent updating of rules. Many applications require that the classification rules be derived from data representing exemplar occurrences of data patterns belonging to different classes. The problem of identifying such rules in data has been researched within the field of machine learning, and more recently in the context of rough set theory and knowledge discovery in databases. In this paper we present an incremental methodology for finding all maximally generalized rules and for adaptive modification of them when new data become available. The methodology is developed in the context of rough set theory and is based on the earlier idea of discernibility matrix introduced by Skowron.
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Automated knowledge acquisition is an important research issue in machine learning. Several methods of inductive learning, such as ID3 family and AQ family, have been applied to discover meaningful knowledge from large databases and their usefulness is assured in several aspects. However, since their methods are of a deterministic nature and the reliability of acquired knowledge is not evaluated statistically, these methods are ineffective when applied to domains essentially probabilistic in nature, such as medical domains. Extending concepts of rough set theory to a probabilistic domain, we introduce a new approach to knowledge acquisition, which induces probabilistic rules based on rough set theory (PRIMEROSE) and develop a program that extracts rules for an expert system from a clinical database, using this method. The results show that the derived rules almost correspond to those of the medical experts.
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  • 81
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In this paper we present various logical characterizations of justification-based (nonmonotonic) truth maintenance systems (JTMS). These characterizations, which are proved to be equivalent, aim at describing dependency-directed backtracking (DDB) (i.e., the process of resolving conflicts which can arise when nogoods are allowed in the set of justifications), mainly relying on the intuitive idea that a contrapositrve use of justifications is needed to resolve inconsistencies. The idea is first formalized by means of the notion of three-valued labeling and then through a transformation which explicitly adds all contrapositives of the justifications. An abductive characterization of the JTMS is provided through a further transformation which converts a set of nonmonotonic justifications to a corresponding abduction framework. This approach provides a unifying framework, based on the notion of abduction, for describing both JTMSs and assumption-based TMSs (ATMSs).
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  • 82
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Negotiations are very important in a multiagenl environment, particularly, in an environment where there are conflicts between the agents, and cooperation would be beneficial. We have developed a general structure for a Negotiating Automated Agent that consists of five modules: a Prime Minister, a Ministry of Defense, a Foreign Office, a Headquarters and Intelligence. These modules are implemented using a dynamic set of local agents belonging to the different modules. We used this structure to develop a Diplomacy player. Diplomat. Playing Diplomacy involves a certain amount of technical skills as in other board games, but the capacity to negotiate, explain, convince, promise, keep promises or break them, is an essential ingredient in good play. Diplomat was evaluated and consistently played better than human players.
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  • 83
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The general use of subjective probabilities to model beliefs has been justified using many axiomatic schemes. This paper presents a rationale for probability models based on intuitive properties of belief orderings and the effect of evidence on beliefs. Qualitative probability, which imposes stringent constraints on belief representation schemes, is derived from four simple assumptions about beliefs and evidence. Properties shown to be sufficient for the adoption of probability proper by Cox (1978) are derived here from qualitative probability and a principle of plausible reasoning advanced by Polya (1954). Models based on complete orderings of beliefs extend easily to motivate set-valued representations of partial orderings as well.
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  • 84
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In this paper, we present VSTA, our Prolog-based verifier, for formal specification and verification of systolic architectures. VSTA allows users to design systolic array architectures in the STA specification language (STA was developed earlier by Ling for formal description and reasoning of systolic designs) and semi-automatically verifies these designs The implementation of VSTA is based on a standard Prolog system. Its interface uses Motif system calls based on the X11 and UNIX environments. VSTA provides facilities to assist the user in the design of systolic array specifications. The system allows a formal proof to be derived interactively with suggestions from the user. The proof techniques used are mathematical induction and rewriting. The induction technique is adopted to exploit the regularity and locality nature of systolic array architectures. A number of verification tactics are developed and their operational rules are used in the verifier. Using the powerful symbolic computation ability of Prolog, particularly pattern matching, automatic backtracking, and depth-first searching, the verifier performs efficiently in the construction of proofs. We also describe the strategies we used in proving a matrix multiplication systolic array and an LU decomposition systolic array.
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  • 85
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Finding the referent of a definite noun phrase is a classic problem in natural language processing. Most work assumes that when a program begins to analyze an utterance, it already has the knowledge it needs for identifying referents. If a robot accepts commands in natural language, this assumption may not hold. Suppose a user says, “Go get the book on the table in room 3,” but the robot has never been in room 3, so it lacks the knowledge it needs to identify the referent of “the book on the table in room 3.” To gain this knowledge, the robot must travel to room 3 and search. This article describes a simulated robot that accepts commands in English and actively searches for the referents of definite descriptions.
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  • 86
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The epistemic notions of knowledge and belief have most commonly been modeled by means of possible worlds semantics. In such approaches an agent knows (or believes) all logical consequences of its beliefs. Consequently, several approaches have been proposed to model systems of explicit belief, more suited to modeling finite agents or computers. In this paper a general framework is developed for the specification of logics of explicit belief. A generalization of possible worlds, called situations, is adopted. However the notion of an accessibility relation is not employed; instead a sentence is believed if the explicit proposition expressed by the sentence appears among a set of propositions associated with an agent at a situation. Since explicit propositions may be taken as corresponding to “belief contexts” or “frames of mind,” the framework also provides a setting for investigating such approaches to belief. The approach provides a uniform and flexible basis from which various issues of explicit belief may be addressed and from which systems may be contrasted and compared. A family of logics is developed using this framework, which extends previous approaches and addresses issues raised by these earlier approaches. The more interesting of these logics are tractable, in that determining if a belief follows from a set of beliefs, given certain assumptions, can be accomplished in polynomial time.
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  • 87
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 11 (1995), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Ordered model trees were introduced as a normal form for disjunctive deductive databases. They were also used to facilitate the computation of minimal models for disjunctive theories by exploiting the order imposed on the Herbrand base of the theory. In this work we show how the order on the Herbrand base can be used to compute perfect models of a disjunctive stratified finite theory. We are able to compute the stable models of a general finite theory by combining the order on the elements of the Herbrand base with previous results that had shown that the stable models of a theory T can be computed as the perfect models of a corresponding disjunctive theory ɛT resulting from applying the so called evidential transformation to T. While other methods consider many models that are rejected at the end, the use of atom ordering allows us to guarantee that every model generated belongs to the class of models being computed. As for negation-free databases, the ordered tree serves as the canonical representation of the database.
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  • 88
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 89
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 90
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    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.
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  • 91
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 92
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
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  • 93
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
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  • 95
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    Expert systems 12 (1995), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 96
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    Springer
    Mathematical programming 68 (1995), S. 105-130 
    ISSN: 1436-4646
    Keywords: primary 49B34 ; secondary 90C31 ; 93C30 ; Variational inequalities ; Sensitivity analysis ; Generalized Jacobian
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Optimization problems with variational inequality constraints are converted to constrained minimization of a local Lipschitz function. To this minimization a non-differentiable optimization method is used; the required subgradients of the objective are computed by means of a special adjoint equation. Besides tests with some academic examples, the approach is applied to the computation of the Stackelberg—Cournot—Nash equilibria and to the numerical solution of a class of quasi-variational inequalities.
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  • 97
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    Mathematical programming 69 (1995), S. 1-43 
    ISSN: 1436-4646
    Keywords: Mathematical programming ; Cutting planes ; Analytic center
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Anoracle for a convex setS ⊂ ℝ n accepts as input any pointz in ℝ n , and ifz ∈S, then it returns ‘yes’, while ifz ∉S, then it returns ‘no’ along with a separating hyperplane. We give a new algorithm that finds a feasible point inS in cases where an oracle is available. Our algorithm uses the analytic center of a polytope as test point, and successively modifies the polytope with the separating hyperplanes returned by the oracle. The key to establishing convergence is that hyperplanes judged to be ‘unimportant’ are pruned from the polytope. If a ball of radius 2−L is contained inS, andS is contained in a cube of side 2 L+1, then we can show our algorithm converges after O(nL 2) iterations and performs a total of O(n 4 L 3+TnL 2) arithmetic operations, whereT is the number of arithmetic operations required for a call to the oracle. The bound is independent of the number of hyperplanes generated in the algorithm. An important application in which an oracle is available is minimizing a convex function overS.
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  • 98
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    Mathematical programming 69 (1995), S. 45-73 
    ISSN: 1436-4646
    Keywords: Cutting plane ; Stochastic programming ; Analytic center ; Interior-point method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The stochastic linear programming problem with recourse has a dual block-angular structure. It can thus be handled by Benders' decomposition or by Kelley's method of cutting planes; equivalently the dual problem has a primal block-angular structure and can be handled by Dantzig-Wolfe decomposition—the two approaches are in fact identical by duality. Here we shall investigate the use of the method of cutting planes from analytic centers applied to similar formulations. The only significant difference form the aforementioned methods is that new cutting planes (or columns, by duality) will be generated not from the optimum of the linear programming relaxation, but from the analytic center of the set of localization.
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  • 99
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    Mathematical programming 69 (1995), S. 237-253 
    ISSN: 1436-4646
    Keywords: Variational inequality ; Nonlinear complementarity ; Nonlinear programming ; Continuation method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper presents a continuation method for monotone variational inequality problems based on a new smooth equation formulation. The existence, uniqueness and limiting behavior of the path generated by the method are analyzed.
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  • 100
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    Mathematical programming 69 (1995), S. 269-309 
    ISSN: 1436-4646
    Keywords: Quadratic programming ; Submodular constraints ; Kuhn-Tucker conditions ; Lexicographically optimal flow ; Parametric maximum flow
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We present new strongly polynomial algorithms for special cases of convex separable quadratic minimization over submodular constraints. The main results are: an O(NM log(N 2/M)) algorithm for the problemNetwork defined on a network onM arcs andN nodes; an O(n logn) algorithm for thetree problem onn variables; an O(n logn) algorithm for theNested problem, and a linear time algorithm for theGeneralized Upper Bound problem. These algorithms are the best known so far for these problems. The status of the general problem and open questions are presented as well.
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