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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement

February 1, 2023

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Authors

Qi Zhang

University of Michigan


Edmund Durfee

University of Michigan


Satinder Singh

University of Michigan


DOI:

10.1609/aaai.v34i06.6596


Abstract:

Most research on probabilistic commitments focuses on commitments to achieve enabling preconditions for other agents. Our work reveals that probabilistic commitments to instead maintain preconditions for others are surprisingly harder to use well than their achievement counterparts, despite strong semantic similarities. We isolate the key difference as being not in how the commitment provider is constrained, but rather in how the commitment recipient can locally use the commitment specification to approximately model the provider's effects on the preconditions of interest. Our theoretic analyses show that we can more tightly bound the potential suboptimality due to approximate modeling for achievement than for maintenance commitments. We empirically evaluate alternative approximate modeling strategies, confirming that probabilistic maintenance commitments are qualitatively more challenging for the recipient to model well, and indicating the need for more detailed specifications that can sacrifice some of the agents' autonomy.

Topics: AAAI

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HOW TO CITE:

Qi Zhang||Edmund Durfee||Satinder Singh Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement Proceedings of the AAAI Conference on Artificial Intelligence (2020) 10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement AAAI 2020, 10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh (2020). Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement. Proceedings of the AAAI Conference on Artificial Intelligence, 10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh. Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh. 2020. Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement. "Proceedings of the AAAI Conference on Artificial Intelligence". 10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh. (2020) "Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement", Proceedings of the AAAI Conference on Artificial Intelligence, p.10326-10333

Qi Zhang||Edmund Durfee||Satinder Singh, "Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement", AAAI, p.10326-10333, 2020.

Qi Zhang||Edmund Durfee||Satinder Singh. "Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh. "Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 10326-10333.

Qi Zhang||Edmund Durfee||Satinder Singh. Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement. AAAI[Internet]. 2020[cited 2023]; 10326-10333.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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