A general representation and approximate inference algorithm for sensing actions

Authors:
Hanne Vlaeminck;Joost Vennekens;Marc Denecker
Affiliations:
Department of Computer Science, KU Leuven, Belgium;Department of Computer Science, KU Leuven, Belgium, Campus De Nayer, Lessius Mechelen, Sint-Katelijne-Waver, Belgium;Department of Computer Science, KU Leuven, Belgium
Venue:
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Year:
2012

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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.