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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    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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  • 3
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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.
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  • 4
    Electronic Resource
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    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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  • 5
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    ISSN: 1467-8640
    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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  • 6
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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.
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  • 7
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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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  • 8
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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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  • 9
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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.
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  • 10
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 12 (1996), S. 0 
    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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  • 11
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 12
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Open Distributed Systems Jon Crowcrofi
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  • 13
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 14
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    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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  • 15
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 16
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    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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  • 17
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    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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  • 18
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    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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  • 19
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 20
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 21
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 22
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    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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  • 23
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    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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  • 24
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 25
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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  • 26
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    Oxford, UK : Blackwell Publishing Ltd
    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 27
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    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 28
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    Expert systems 13 (1996), S. 0 
    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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    Expert systems 13 (1996), S. 0 
    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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    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
    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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    Expert systems 13 (1996), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
    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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    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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    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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    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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    Computational intelligence 12 (1996), S. 0 
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    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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    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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    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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    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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    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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    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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    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.
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    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.
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    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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    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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    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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    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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    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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    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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    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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    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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