Conference Proceedings

Adapting novelty to classical planning as heuristic search

M Katz, D Moshkovich, N Lipovetzky, A Tüisov

Proceedings International Conference on Automated Planning and Scheduling, ICAPS | Association for the Advancement of Artificial Intelligence | Published : 2017

Abstract

Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. The introduction of the concept of state novelty has advanced the state of the art in deterministic online planning in Atarilike 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..

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Grants

Awarded by Australian Research Council


Funding Acknowledgements

The work was performed, in part, while A. Tuisov was a summer intern at IBM Watson Health, Israel. The work by N. Lipovetzky is partially supported by the Australian Research Council linkage grant LP11010015.