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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 > No. 9: AAAI-22 Technical Tracks 9

Planning to Avoid Side Effects

Authors

Toryn Q. Klassen

Department of Computer Science, University of Toronto, Toronto, Canada Vector Institute for Artificial Intelligence, Toronto, Canada Schwartz Reisman Institute for Technology and Society, Toronto, Canada


Sheila A. McIlraith

Department of Computer Science, University of Toronto, Toronto, Canada Vector Institute for Artificial Intelligence, Toronto, Canada Schwartz Reisman Institute for Technology and Society, Toronto, Canada


Christian Muise

School of Computing, Queen's University, Kingston, Canada


Jarvis Xu

School of Computing, Queen's University, Kingston, Canada


Proceedings:

No. 9: AAAI-22 Technical Tracks 9

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

AAAI Technical Track on Planning, Routing, and Scheduling

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Abstract:

In sequential decision making, objective specifications are often underspecified or incomplete, neglecting to take into account potential (negative) side effects. Executing plans without consideration of their side effects can lead to catastrophic outcomes -- a concern recently raised in relation to the safety of AI. In this paper we investigate how to avoid side effects in a symbolic planning setting. We study the notion of minimizing side effects in the context of a planning environment where multiple independent agents co-exist. We define (classes of) negative side effects in terms of their effect on the agency of those other agents. Finally, we show how plans which minimize side effects of different types can be computed via compilations to cost-optimizing symbolic planning, and investigate experimentally.

DOI:

10.1609/aaai.v36i9.21219


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36