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Marvin: a heuristic search planner with online macro-action learning. (English) Zbl 1182.68231
Summary: This paper describes Marvin, a planner that competed in the Fourth International Planning Competition (IPC 4). Marvin uses action-sequence-memoisation techniques to generate macro-actions, which are then used during search for a solution plan. We provide an overview of its architecture and search behaviour, detailing the algorithms used. We also empirically demonstrate the effectiveness of its features in various planning domains; in particular, the effects on performance due to the use of macro-actions, the novel features of its search behaviour, and the native support of ADL and Derived Predicates.

68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T05 Learning and adaptive systems in artificial intelligence
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