Skip to main content
Article
Knowledge-Based Search in Competitive Domains
IEEE Transactions on Knowledge and Data Engineering
  • Steven Walczak, University of South Florida
Document Type
Article
Publication Date
6-1-2003
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.

Citation / Publisher Attribution

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

Citation Information
Steven Walczak. "Knowledge-Based Search in Competitive Domains" IEEE Transactions on Knowledge and Data Engineering Vol. 15 Iss. 3 (2003) p. 734 - 743
Available at: http://works.bepress.com/steven-walczak/41/