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 lawsuits of the thirteenth Biennial convention of the Canadian Society for Computational reports of Intelligence, AI 2000, held in Montreal, Quebec, Canada, in could 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 geared up in topical sections on video games and constraint delight; ordinary language processing; wisdom illustration; AI purposes; laptop studying and knowledge mining; making plans, theorem proving, and synthetic lifestyles; and neural networks.

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Additional 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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Constraint directed backtracking. In A. Sattar, editor, Advanced Topics in AI, pages 47–56. Springer Verlag, 1997. Volume 1342, LNAI. [13] W. Pang and S. Goodwin. Characterizing tractable csps. In Proceedings of AI’98, the Twelfth Canadian Conference on Artificial Intelligence, pages 259–272, 1998. [14] F. Rossi, C. Petrie, and V. Dhar. On the equivalence of constraint satisfaction problems. In Proceedings of the 9th European Conference on Artificial Intelligence, pages 550–556, 1990. [15] J. Thornton and A.

Hard constraints must be satisfied while soft constraints may be violated. Graph theoretic properties of constraint networks have been used to develop algorithms for constraint solving [5, 6]. Among these, algorithms that are based on one of two representations, the primal constraint graph and the dual constraint graph [5, 6] are more common. Structure driven algorithms that are constructed from the primal constraint graph (a generalisation of a simple binary constraint graph) have lead to chronological backtracking based solvers that incrementally instantiate variables with values and backtrack when dead-ends are encountered.

Total potentials 4 Search Queenbee uses an iterative deepening α-β search enhanced with Minimal Window / Principal Variation Search and transposition tables. These techniques are used in most state-of-the-art game playing programs [Mar86]. The move ordering is based on cell potentials. Queenbee’s search incorporates the fractional ply searching ideas of the “Sex Search algorithm” [LBT89]. 1 Jack van Rijswijck Sex Search The large branching factor of Hex makes regular full-width searching methods inadequate, even when enhanced with conventional search extensions and reductions.

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