2024 AAAI AAAI 2024

Towards Epistemic-Doxastic Planning with Observation and Revision

Abstract

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.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Knowledge & Reasoning
🧭 Keyword Pioneer — knowledge and belief
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics