New PDF release: Advances in Case-Based Reasoning: 8th European Conference,

By Edwina L. Rissland (auth.), Thomas R. Roth-Berghofer, Mehmet H. Göker, H. Altay Güvenir (eds.)

ISBN-10: 3540368434

ISBN-13: 9783540368434

This booklet constitutes the refereed complaints of the eighth ecu convention on Case-Based Reasoning, ECCBR 2004, held in Fethiye, Turkey in September 2006.

The 31 revised complete papers and five revised program papers awarded including 2 invited papers and a pair of abstracts of invited talks have been conscientiously reviewed and chosen from various submissions. All present concerns in case-based reasoning, starting from theoretical and methodological concerns to complicated functions in a number of fields are addressed, hence providing a consultant photograph of present CBR research.

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Additional info for Advances in Case-Based Reasoning: 8th European Conference, ECCBR 2006 Fethiye, Turkey, September 4-7, 2006 Proceedings

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Proof. , a7 such that for 1 ≤ i ≤ 7, ai = 1 in all cases with the following exceptions: (1) for 1 ≤ i ≤ 6, ai = 0 in Ck+1, (2) for 1 ≤ i ≤ k, ai = 0 in Ci, and (3) for 1 ≤ i ≤ k, a7 = 0 in Ci. For k = 1, the cases in the resulting case base are: C1 = (0, 1, 1, 1, 1, 1, 0), C2 = (0, 0, 0, 0, 0, 0, 1) Now consider the query Q = {ai = 1: 1 ≤ i ≤ 7}. As Sim(Ci, Q) = and Sim(Ck+1, Q) = 5 for 1 ≤ i ≤ k, 7 1 , the k-NN retrieval set includes all cases in the case base except 7 Ck+1. It is also clear that the similarities of all cases in the k-NN retrieval set must lie in same similarity interval.

Not dominated by another object) as an approach to addressing the limitations of retrieval based on exact matching [17-18]. Elimination of dominated alternatives is also a strategy sometimes used to reduce the number of candidates to be compared by other methods in multiple criteria decision making [19-20]. With respect to each constraint in a recommender system query, it is reasonable to assume that any case that satisfies the constraint is preferred to one that does not satisfy the constraint.

One main difference is, however, that this experience is not processed mathematically into some kind of value function, but explicitly stored in the system’s case base. Furthermore, it is rather unusual to speak of autonomous agents in CBR settings. This difference, however, is of minor importance, since it represents a question of notion and reflects only two different views of describing how the system acquires its experience. Multi-agent domains in which autonomous agents act entirely independently are faced with the problem that the agents behave without any form of central control in a shared environment, having the goal to learn a behaviour policy that is optimal for the respective environment.

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Advances in Case-Based Reasoning: 8th European Conference, ECCBR 2006 Fethiye, Turkey, September 4-7, 2006 Proceedings by Edwina L. Rissland (auth.), Thomas R. Roth-Berghofer, Mehmet H. Göker, H. Altay Güvenir (eds.)


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