Representing and planning with interacting actions and privacy

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Publication:  Artificial Intelligence

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Tags:     AI

Abstract

Interacting actions – actions whose joint effect differs from the union of their individual effects – are challenging both to represent and to plan with due to their combinatorial nature. So far, there have been few attempts to provide a succinct language for representing them that can also support efficient centralized planning and distributed privacy preserving planning. In this paper we suggest an approach for representing interacting actions succinctly and show how such a domain model can be compiled into a standard single-agent planning problem as well as to privacy preserving multi-agent planning. We test the performance of our method on a number of novel domains involving interacting actions and privacy.

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https://doi.org/10.1016/j.artint.2019.103200

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