Synthesizing strategies under expected and exceptional environment behaviors

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

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