Synthesizing strategies under expected and exceptional environment behaviors

Benjamin Aminof, Giuseppe De Giacomo, Alessio Lomuscio, Aniello Murano, Sasha Rubin

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Main track. Pages 1674-1680.

https://doi.org/10.24963/ijcai.2020/232

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Abstract

We consider an agent that operates with two models of the environment: one that captures expected behaviors and one that captures additional exceptional behaviors. We study the problem of synthesizing agent strategies that enforce a goal against environments operating as expected while also making a best effort against exceptional environment behaviors. We formalize these concepts in the context of linear-temporal logic, and give an algorithm for solving this problem. We also show that there is no trade-off between enforcing the goal under the expected environment specification and making a best-effort for it under the exceptional one.

Keywords

  • Knowledge Representation and Reasoning: Action, Change and Causality
  • Planning and Scheduling: Theoretical Foundations of Planning
  • Agent-based and Multi-agent Systems: Formal Verification, Validation and Synthesis
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