Evaluating the Effectiveness of Exploration and Accumulated Experience in Automatic Case Elicitation

Autor:	Brandon M. Hauff, Jay Powell, John D. Hastings
Rok vydání:	2005
Předmět:	Reasoning system Empirical research Human–computer interaction Computer science business.industry Domain knowledge Artificial intelligence business Domain (software engineering)
Zdroj:	Case-Based Reasoning Research and Development ISBN: 9783540281740 ICCBR
DOI:	10.1007/11536406_31
Popis:	Non-learning problem solvers have been applied to many interesting and complex domains. Experience-based learning techniques have been developed to augment the capabilities of certain non-learning problem solvers in order to improve overall performance. An alternative approach to enhancing pre-existing systems is automatic case elicitation, a learning technique in which a case-based reasoning system with no prior domain knowledge acquires knowledge automatically through real-time exploration and interaction with its environment. In empirical testing in the domain of checkers, results suggest not only that experience can substitute for the inclusion of pre-coded model-based knowledge, but also that the ability to explore is crucial to the performance of automatic case elicitation.
Databáze:	OpenAIRE
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