Title

Knowledge-Based Search in Competitive Domains

Document Type

Article

Publication Date

6-1-2003

Keywords

search, knowledge-based, chunking, opponent modeling, heuristic pruning, chess

Digital Object Identifier (DOI)

http://dx.doi.org/10.1109/tkde.2003.1198402

Abstract

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 modeling 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 domains such as aerial combat or corporate takeovers.

Comments

This article was written before Steven Walczak was affiliated with the University of South Florida.

Was this content written or created while at USF?

false

Citation / Publisher Attribution

IEEE Transactions on Knowledge and Data Engineering, v. 15, issue 3, p. 734-743