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• W2056574246 abstract "Abstract The main contribution of this paper is a new domain-independent explanation-based learning (EBL) algorithm. The new EBL∗DI algorithm significantly outperforms traditional EBL algorithms both by learning in situations where traditional algorithms cannot learn as well as by providing greater problem-solving performance improvement in general. The superiority of the EBL∗DI algorithm is demonstrated with experiments in three different application domains. The EBL∗DI algorithm is developed using a novel formal framework in which traditional EBL techniques are reconstructed as the structured application of three explanation-transformation operators. We extend this basic framework by introducing two additional operators that, when combined with the first three operators, allow us to prove a completeness result: in the formal framework, every EBL algorithm is equivalent to the application of the five transformation operators according to some control strategy. The EBL∗DI algorithm employs all five proof-transformation operators guided by five domain-independent control heuristics." @default.
• W2056574246 created "2016-06-24" @default.
• W2056574246 creator A5038246567 @default.
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• W2056574246 date "1994-09-01" @default.
• W2056574246 modified "2023-09-24" @default.
• W2056574246 title "A high-performance explanation-based learning algorithm" @default.
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• W2056574246 doi "https://doi.org/10.1016/0004-3702(94)90077-9" @default.
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