A general representation and approximate inference algorithm for sensing actions

摘要: 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 representing both changes real world and of agent, based on first order linear time calculus. Our is more than most existing approaches, because our semantics explicitly represents, each point in time, not only agent's that timepoint, but also past future. By applying approximation method classical logic framework, obtain efficient sound incomplete reasoning method.