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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

How to Reduce Action Space for Planning Domains? (Student Abstract)

February 1, 2023

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Authors

Harsha Kokel

The University of Texas at Dallas


Junkyu Lee

IBM Research


Michael Katz

IBM Research


Shirin Sohrabi

IBM Research


Kavitha Srinivas

IBM Research


DOI:

10.1609/aaai.v36i11.21631


Abstract:

While AI planning and Reinforcement Learning (RL) solve sequential decision-making problems, they are based on different formalisms, which leads to a significant difference in their action spaces. When solving planning problems using RL algorithms, we have observed that a naive translation of the planning action space incurs severe degradation in sample complexity. In practice, those action spaces are often engineered manually in a domain-specific manner. In this abstract, we present a method that reduces the parameters of operators in AI planning domains by introducing a parameter seed set problem and casting it as a classical planning task. Our experiment shows that our proposed method significantly reduces the number of actions in the RL environments originating from AI planning domains.

Topics: AAAI

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HOW TO CITE:

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas How to Reduce Action Space for Planning Domains? (Student Abstract) Proceedings of the AAAI Conference on Artificial Intelligence (2022) 12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas How to Reduce Action Space for Planning Domains? (Student Abstract) AAAI 2022, 12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas (2022). How to Reduce Action Space for Planning Domains? (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. How to Reduce Action Space for Planning Domains? (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. 2022. How to Reduce Action Space for Planning Domains? (Student Abstract). "Proceedings of the AAAI Conference on Artificial Intelligence". 12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. (2022) "How to Reduce Action Space for Planning Domains? (Student Abstract)", Proceedings of the AAAI Conference on Artificial Intelligence, p.12989-12990

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas, "How to Reduce Action Space for Planning Domains? (Student Abstract)", AAAI, p.12989-12990, 2022.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. "How to Reduce Action Space for Planning Domains? (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. "How to Reduce Action Space for Planning Domains? (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 12989-12990.

Harsha Kokel||Junkyu Lee||Michael Katz||Shirin Sohrabi||Kavitha Srinivas. How to Reduce Action Space for Planning Domains? (Student Abstract). AAAI[Internet]. 2022[cited 2023]; 12989-12990.


ISSN: 2374-3468


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