Generalizing and Executing Plans

Authors

  • Christian Muise University of Toronto

DOI:

https://doi.org/10.1609/aaai.v26i1.8195

Keywords:

automated planning, generalized planning, execution monitoring

Abstract

In a dynamic environment, an intelligent agent must consider unexpected changes to the world and plan for them. We aim to address this key issue by building more robust artificial agents through the generalization of plan representations. Our research focuses on the process of generalizing various plan forms and the development of a compact representation which embodies a generalized plan as a policy. Our techniques allow an agent to execute efficiently in an online setting. We have, to date, demonstrated our approach for sequential and partial order plans and are pursuing similar techniques for representations such as Hierarchical Task Networks and GOLOG programs

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Published

2021-09-20

How to Cite

Muise, C. (2021). Generalizing and Executing Plans. Proceedings of the AAAI Conference on Artificial Intelligence, 26(1), 2398-2399. https://doi.org/10.1609/aaai.v26i1.8195