Download Advances in Artificial Intelligence: 13th Biennial by Jonathan Schaeffer, Aske Plaat (auth.), Howard J. Hamilton PDF

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

This e-book constitutes the refereed court cases of the thirteenth Biennial convention of the Canadian Society for Computational reviews of Intelligence, AI 2000, held in Montreal, Quebec, Canada, in may well 2000. The 25 revised complete papers offered 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; traditional language processing; wisdom illustration; AI purposes; computer studying and knowledge mining; making plans, theorem proving, and synthetic lifestyles; and neural networks.

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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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6 The median solution length for these positions was 22 ply. The depth of a win is not necessarily what makes a position hard to solve. If the winning move is obviously better than the other moves, particularly if all other moves lose quickly, the solution is not difficult to see. However, in the positions used in the test, the longest losing lines had a median length of 17 and a maximum length of 23. The correct decision between such deep wins and deep losses is extremely difficult to find. It should also be noted that these are all winning positions at the beginning of the game, and as such they are the most difficult of all 6 × 6 Hex problems.

A move cost of k effectively extends the search by 1 − k ply if k < 1, and reduces the search by k − 1 ply if k > 1. If the range of costs of the available moves is large, then the Sex Search algorithm behaves much like a selective search. Consider, for example, a move m with cost 4. This cost ensures that the subtree below m will be explored to a depth of 3 less than the subtrees below m’s siblings. Due to the exponential nature of the search tree, the search effort required to explore m becomes insignificant in comparison with the effort required to explore m’s siblings.

For the task of extracting keyphrases, full, detailed parses of complete English sentences are not needed. To avoid the overhead associated with deep parsing, we decided to implement a simple base noun phrase skimmer instead. A base noun phrase is a non-recursive structure consisting of a head noun and zero or more premodifying adjectives and/or nouns. The base noun phrase does not include noun phrase postmodifiers such as prepositional phrases or relative clauses. 1 Such a skimmer requires knowledge of the parts of speech of the words in the text.

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