A General Representation and Approximate Inference Algorithm for Sensing Actions

Hanne Vlaeminck¹, Joost Vennekens^{1, 2}, and Marc Denecker¹

¹Department of Computer Science, KU Leuven, Belgium

²Campus De Nayer, Lessius Mechelen, Sint-Katelijne-Waver, Belgium

Abstract. Sensing actions, which allow an agent to increase its knowledge about the environment, are problematic for traditional planning languages. In this paper we propose a very general framework for representing both changes to the real world and to the knowledge of an agent, based on a first order linear time calculus. Our framework is more general than most existing approaches, because our semantics explicitly represents, for each point in time, not only the agent’s knowledge about that timepoint, but also about the past and the future. By applying a general approximation method for classical logic to this framework, we obtain an efficient and sound but incomplete reasoning method.

LNAI 7691, p. 543 ff.

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