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Knowledge-based search in competitive domains
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DOI：10.1109/TKDE.2003.1198402.png)
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摘要
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Artificial Intelligence programs operating in competitive domains typically use brute-force search if the domain can be modeled using a search tree or alternately use nonsearch heuristics as in production rule-based expert systems. While brute-force techniques have recently proven to be a viable method for modelin g domains with smaller search spaces, such as checkers and chess, the same techniques cannot succeed in more complex, domains, such as shogi or go. This research uses a cognitive-based modeling strategy to develop a heuristic search technique based on cognitive thought processes With minimal domain specific knowledge. The cognitive-based search technique provides a-significant reduction in search space complexity and, furthermore enables the search paradigms to be extended to domains that are not typically thought of as search domain's such as aerial combat or corporate takeovers.
Keyword:
search
knowledge-based
chunking
opponent modeling
heuristic pruning
chess
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