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

ISBN-10: 3540454861

ISBN-13: 9783540454861

ISBN-10: 3540675574

ISBN-13: 9783540675570

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

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Additional resources 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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Fortunately, zugzwang does not occur in Hex. Any move is always better than no move at all. Null move therefore promises to be a powerful enhancement of the search in Queenbee. Efforts are underway to construct a Java interface that enables Queenbee to play games online on its own web page. This will not only provide valuable feedback on the program’s playing strength, but it will also facilitate the learning of move category weights. 7 Conclusions The comparison with perfect information on a 6 × 6 board is a favourable indication of the quality of the evaluation function.

Categories can be assigned low or high weights according to whether good moves are relatively common or uncommon, respectively. The bottom row of Table 1 indicates that almost all categories do show a large deviation from the average frequency. Moreover, the frequency of optimal moves decreases almost monotonically as the move category increases, indicating that the cell potential is indeed a good estimator of move strength. position type move type ≤ −3 -2 -1 optimal - 25 13 winning suboptimal good - 25 13 bad - 75 88 count - 4 8 losing optimal 100 100 100 suboptimal count 3 3 5 all optimal 100 57 46 0 25 22 47 53 60 35 65 63 30 1 11 6 17 83 71 6 94 62 9 move category 2 3 4 5 2 7 2 4 20 6 6 8 22 14 8 12 78 86 92 88 134 140 171 131 1 1 0 99 99 100 100 139 203 213 178 2 4 1 1 6 3 3 97 113 100 148 - 7 ≥ 8 all 5 7 11 100 100 89 39 19 890 4 100 100 96 56 76 1149 4 Table 1.

On the other hand, it should be noted that perfect play on a 6 × 6 board is far from trivial. One piece of anecdotal evidence is that Queenbee has actually disproved some of the common beliefs of strong Hex players about certain opening moves. Equipped with the perfect opening book and a powerful search to fill in the blanks where the opening book ends, Queenbee plays stronger than any human player on board sizes up to 6 × 6. On larger boards, human players’ supremacy increases as the board size increases.

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


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