Towards Epistemic-Doxastic Planning with Observation and Revision
Thorsten Engesser, Andreas Herzig, Elise Perrotin
Abstract
Epistemic planning is useful in situations where multiple agents have different knowledge and beliefs about the world, such as in robot-human interaction. One aspect that has been largely neglected in the literature is planning with observations in the presence of false beliefs. This is a particularly challenging problem because it requires belief revision. We introduce a simple specification language for reasoning about actions with knowledge and belief. We demonstrate our approach on well-known false-belief tasks such as the Sally-Anne Task and compare it to other action languages. Our logic leads to an epistemic planning formalism that is expressive enough to model second-order false-belief tasks, yet has the same computational complexity as classical planning.
BibTeX
@article{Engesser_Herzig_Perrotin_2024, title={Towards Epistemic-Doxastic Planning with Observation and Revision}, volume={38}, url={https://ojs.aaai.org/index.php/AAAI/article/view/28919}, DOI={10.1609/aaai.v38i9.28919}, abstractNote={Epistemic planning is useful in situations where multiple agents have different knowledge and beliefs about the world, such as in robot-human interaction. One aspect that has been largely neglected in the literature is planning with observations in the presence of false beliefs. This is a particularly challenging problem because it requires belief revision. We introduce a simple specification language for reasoning about actions with knowledge and belief. We demonstrate our approach on well-known false-belief tasks such as the Sally-Anne Task and compare it to other action languages. Our logic leads to an epistemic planning formalism that is expressive enough to model second-order false-belief tasks, yet has the same computational complexity as classical planning.}, number={9}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Engesser, Thorsten and Herzig, Andreas and Perrotin, Elise}, year={2024}, month={Mar.}, pages={10501-10508} }