Experimental comparison of human and machine learning formalisms
作者： Stephen Muggleton , Michael Bain , Jean Hayes-Michie , Donald Michie
DOI: 10.1016/B978-1-55860-036-2.50037-0
关键词:
摘要: In this paper we describe the results of a set experiments in which compared learning performance human and machine agents. The problem involved concept description for deciding on legality positions within chess endgame King Rook against King. Various amounts background knowledge were made available to each agent. We concluded that ability produce high domain was almost entirely dependent express first-order predicate relationships.
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