Knowledge-Based Search in Competitive Domains
Document Type
Article
Publication Date
6-2003
Keywords
Artificial intelligence, Books, Humans, Competitive intelligence, Production systems, Expert systems, Hardware, Circuit analysis computing, Concurrent computing, Iterative methods
Digital Object Identifier (DOI)
https://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.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
IEEE Transactions on Knowledge and Data Engineering, v. 15, issue 3, p. 734-743
Scholar Commons Citation
Walczak, Steven, "Knowledge-Based Search in Competitive Domains" (2003). School of Information Faculty Publications. 194.
https://digitalcommons.usf.edu/si_facpub/194
