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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Learning Features and Abstract Actions for Computing Generalized Plans

February 1, 2023

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Authors

Blai Bonet

Universidad Simon Bolivar


Guillem Francès

University of Basel


Hector Geffner

Universitat Pompeu Fabra


DOI:

10.1609/aaai.v33i01.33012703


Abstract:

Generalized planning is concerned with the computation of plans that solve not one but multiple instances of a planning domain. Recently, it has been shown that generalized plans can be expressed as mappings of feature values into actions, and that they can often be computed with fully observable non-deterministic (FOND) planners. The actions in such plans, however, are not the actions in the instances themselves, which are not necessarily common to other instances, but abstract actions that are defined on a set of common features. The formulation assumes that the features and the abstract actions are given. In this work, we address this limitation by showing how to learn them automatically. The resulting account of generalized planning combines learning and planning in a novel way: a learner, based on a Max SAT formulation, yields the features and abstract actions from sampled state transitions, and a FOND planner uses this information, suitably transformed, to produce the general plans. Correctness guarantees are given and experimental results on several domains are reported.

Topics: AAAI

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HOW TO CITE:

Blai Bonet||Guillem Francès||Hector Geffner Learning Features and Abstract Actions for Computing Generalized Plans Proceedings of the AAAI Conference on Artificial Intelligence (2019) 2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner Learning Features and Abstract Actions for Computing Generalized Plans AAAI 2019, 2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner (2019). Learning Features and Abstract Actions for Computing Generalized Plans. Proceedings of the AAAI Conference on Artificial Intelligence, 2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner. Learning Features and Abstract Actions for Computing Generalized Plans. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner. 2019. Learning Features and Abstract Actions for Computing Generalized Plans. "Proceedings of the AAAI Conference on Artificial Intelligence". 2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner. (2019) "Learning Features and Abstract Actions for Computing Generalized Plans", Proceedings of the AAAI Conference on Artificial Intelligence, p.2703-2710

Blai Bonet||Guillem Francès||Hector Geffner, "Learning Features and Abstract Actions for Computing Generalized Plans", AAAI, p.2703-2710, 2019.

Blai Bonet||Guillem Francès||Hector Geffner. "Learning Features and Abstract Actions for Computing Generalized Plans". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner. "Learning Features and Abstract Actions for Computing Generalized Plans". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 2703-2710.

Blai Bonet||Guillem Francès||Hector Geffner. Learning Features and Abstract Actions for Computing Generalized Plans. AAAI[Internet]. 2019[cited 2023]; 2703-2710.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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