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- W2760525174 abstract "The introduction of the concept of state novelty has advanced the state of the art in deterministic online planning in Atari-like problems and in planning with rewards in general, when rewards are defined on states. In classical planning, however, the success of novelty as the dichotomy between novel and non-novel states was somewhat limited. Until very recently, novelty-based methods were not able to successfully compete with state-of-the-art heuristic search based planners. In this work we adapt the concept of novelty to heuristic search planning, defining the novelty of a state with respect to its heuristic estimate. We extend the dichotomy between novel and non-novel states and quantify the novelty degree of state facts. We then show a variety of heuristics based on the concept of novelty and exploit the recently introduced best-first width search for satisficing classical planning. Finally,we empirically show the resulting planners to significantly improve the state of the art in satisficing planning." @default.
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- W2760525174 date "2017-06-05" @default.
- W2760525174 modified "2023-10-06" @default.
- W2760525174 title "Adapting Novelty to Classical Planning as Heuristic Search" @default.
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- W2760525174 doi "https://doi.org/10.1609/icaps.v27i1.13819" @default.
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