Download e-book for iPad: Advances in Artificial Intelligence: 13th Biennial by Jonathan Schaeffer, Aske Plaat (auth.), Howard J. Hamilton

By Jonathan Schaeffer, Aske Plaat (auth.), Howard J. Hamilton (eds.)

This booklet constitutes the refereed court cases of the thirteenth Biennial convention of the Canadian Society for Computational experiences of Intelligence, AI 2000, held in Montreal, Quebec, Canada, in might 2000. The 25 revised complete papers offered including 12 10-page posters have been conscientiously reviewed and chosen from greater than 70 submissions. The papers are prepared in topical sections on video games and constraint pride; typical language processing; wisdom illustration; AI functions; computer studying and information mining; making plans, theorem proving, and synthetic existence; and neural networks.

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Read Online or Download Advances in Artificial Intelligence: 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000 Montéal, Quebec, Canada, May 14–17, 2000 Proceedings PDF

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Extra info for Advances in Artificial Intelligence: 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000 Montéal, Quebec, Canada, May 14–17, 2000 Proceedings

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26–39, 2000. c Springer-Verlag Berlin Heidelberg 2000 A Constraint Directed Model for Partial Constraint Satisfaction Problems 27 algorithms can also be used to provide partial solutions when there is a fixed bound on computational resources. Here they report the best solutions found so far when the resource bound has been reached. Such algorithms are called anytime algorithms [3]. Freuder and Wallace introduced complete methods with branch and bound as a natural extension to classical backtracking for partial satisfaction.

As before, search concludes when a satisfactory solution is found, or all choices for future values for variables are exhausted. Nodes with a dashed circle around them denote inconsistent nodes, whose level of inconsistency is acceptable. A Constraint Directed Model for Partial Constraint Satisfaction Problems 35 In Figure 5 we show the execution of CDBB on the same example. As before CDBB selects constraints C1 and C2 to form the cover. It visits 4 nodes in all and performs 2 constraint checks.

As before, if a different set of constraints is selected to form the cover, CDBB visits a different number of nodes each time. It turns out that if C1 and C3 are selected, CDBB visits 3 nodes in all, and if C2 C3 are selected it visits 6 nodes in all. The algorithm finds a similar solution that violates 1 constraint. 6 Analysis of CDBB If Ccover is a minimal constraint cover, |Ccover | ≤ |V |. This can be seen by the fact that while selecting constraints to form the cover, each additional constraint, covers at least one new variable, and hence all that is required is a cover of size of at most |V |.

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