Onditional P Lanning : E Pistemic R Easoning about a Ctions with S Ensing and P Robabilities

Mobile robots generally have only incomplete knowledge about their world. This knowledge is augmented through sensing actions. There have been several approaches in reasoning about actions that deal with sensing and knowledge. One important approach, which has been successfully realized on a robotic soccer team, is based on autoepistemic description logics. In this paper, we present a probabilistic generalization of this approach and define a formal semantics through probabilistic transitions between epistemic states. We then present the language PK-PDDL for reasoning about actions with sensing, knowledge, and probabilities, which is given a formal semantics in the above description logic. Furthermore, we formulate the problem of conditional planning under probabilistic uncertainty in this framework, and give an algorithm for optimally solving it, which is based on a reduction to reasoning in description logics. 1Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, I-00198 Rome, Italy; e-mail: fiocchi,lukasiewicz,nardi,[email protected]. 2Alternate address: Institut für Informationssysteme, Technische Universität Wien, Favoritenstraße 9-11, A-1040 Vienna, Austria; e-mail: [email protected]. Acknowledgements: This work has been partially supported by the Austrian Science Fund Project Z29-INF and by a Marie Curie Individual Fellowship of the European Community programme “Human Potential” under contract number HPMF-CT-2001-001286 (Disclaimer: The authors are solely responsible for information communicated and the European Commission is not responsible for any views or results expressed). Copyright c 2003 by the authors INFSYS RR 1843-03-05 I