Synthesizing Strategies Under Expected and Exceptional Environment Behaviors
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.
Cite
Text
Aminof et al. "Synthesizing Strategies Under Expected and Exceptional Environment Behaviors." International Joint Conference on Artificial Intelligence, 2020. doi:10.24963/IJCAI.2020/232Markdown
[Aminof et al. "Synthesizing Strategies Under Expected and Exceptional Environment Behaviors." International Joint Conference on Artificial Intelligence, 2020.](https://mlanthology.org/ijcai/2020/aminof2020ijcai-synthesizing/) doi:10.24963/IJCAI.2020/232BibTeX
@inproceedings{aminof2020ijcai-synthesizing,
title = {{Synthesizing Strategies Under Expected and Exceptional Environment Behaviors}},
author = {Aminof, Benjamin and De Giacomo, Giuseppe and Lomuscio, Alessio and Murano, Aniello and Rubin, Sasha},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2020},
pages = {1674-1680},
doi = {10.24963/IJCAI.2020/232},
url = {https://mlanthology.org/ijcai/2020/aminof2020ijcai-synthesizing/}
}