Titlebook: Research and Development in Intelligent Systems XVII; Proceedings of ES200 Max Bramer,Alun Preece,Frans Coenen Conference proceedings 2001

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Formal Concept Analysis as a Support Technique for CBRowledge embedded in the cases. FCA applied on a case library provides an internal sight of the conceptual structure and allows finding patterns, regularities and exceptions among the cases. Moreover, it extracts certain dependence rules between the attributes describing the cases, that will be used

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An Instance-Based Approach to Pattern Association Learning with Application to the English Past Tensieve exemplars, we introduce a distance metric for pattern association, PAMELA, which extends that used in PEBLS for classification. The associated pattern is then built by adapting that of the retrieved exemplar(s). We show that our algorithm IBPA-3, which uses exemplar distance weighting and attri

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Grouping Multivariate Time Series Variables: Applications to Chemical Process and Visual Field Datas possible. Within this paper, we present a method for decomposing high dimensional MTS into mutually exclusive subsets of variables where within-group dependencies are high and between-group dependencies are low. The method involves the use of two evolutionary computation techniques, which find an

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Genetic Algorithm Behaviour in the Task of Finding the Multi — Maximum Domain global optimum point but also to determine a whole parameter region. Parametric optimisation task is solved and the behaviour of several different real-number genetic algorithms is compared during the solution process. Real number genetic algorithm steps are described and their meaning is explained

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Intelligible AI Planning — Generating Plans Represented as a Set of Constraintstraint reasoners can also be of great help in parts of the planning process. A new more intelligible approach to using AI planning is needed which can use the best “open” styles of planning based on shared plan representations and hierarchical task networks (HTN) and which still allow the use of powerful constraint representations and solvers.

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Incremental Footprint-Based Retrieval and achieves near-optimal competence and quality characteristics. In this paper we describe a simple but important extension to footprint-based retrieval. Empirically we show that this new algorithm can deliver optimal retrieval performance while at the same time retaining the efficiency benefits of the original footprint-based retrieval method.

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Macro and Micro Applications of Case-Based Reasoning to Feature-Based Product Selectionearches, while the macro approach is based on the traditional CBR-cycle but substitutes crisp constraint relaxation for similarity based retrieval. While the discussion is set against the background of a specific case study, the results have a wider applicability across a number of problem domains.