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.
Synthesizing strategies under expected and exceptional environment behaviors / Aminof, Benjamin; De Giacomo, Giuseppe; Lomuscio, Alessio; Murano, Aniello; Rubin, Sasha. - In: IJCAI. - ISSN 1045-0823. - (2020), pp. 1674-1680. (Intervento presentato al convegno Twenty-Ninth International Joint Conference on Artificial Intelligence, (IJCAI 2020) tenutosi a Yokohama, Japan) [10.24963/ijcai.2020/232].
Synthesizing strategies under expected and exceptional environment behaviors
De Giacomo, Giuseppe
;
2020
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.File | Dimensione | Formato | |
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Note: https://doi.org/10.24963/ijcai.2020/232
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