Proceedings

Dynamic Execution of Temporal Plans with Sensing Actions and Bounded Risk

Pedro Henrique Santana, Brian C. Williams

Download BibTeX Cite

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 4393-4393.

Abstract

This thesis focuses on the problem of temporal planning under uncertainty with explicit safety guarantees, which are enforced by means of chance constraints. We aim at elevating the level in which operators interact with autonomous agents and specify their desired behavior, while retaining a keen sensitivity to risk. Instead of relying on unconditional sequences, our goal is to allow contingent plans to be dynamically scheduled and conditioned on observations of the world while remaining safe. Contingencies add flexibility by allowing goals to be achieved through different methods, while observations allow the agent to adapt to the environment. We demonstrate the usefulness of our chance-constrained temporal planning approaches in real-world applications, such as partially observable power supply restoration and collaborative human-robot manufacturing.

Pedro Henrique Santana, and Brian C. Williams. 2015. Dynamic Execution of Temporal Plans with Sensing Actions and Bounded Risk. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 4393–4393. https://ijcai.org/proceedings/2015/644
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards