Representing and Computing Temporally Scoped Beliefs

Steve Hanks

Planning effective courses of action requires making predictions about what the world may be like at the time the actions are to be performed. Making these predictions requires a temporal representation, and-assuming a world that is not entirely predictable and an agent that is not omniscient --a representation of the uncertainty that will characterize its incomplete knowledge of the world. We provide in this paper a representation and calculus for computing an agent’s strength of belief in a proposition at a point in time, based on (possibly imperfect) observations about that proposition and information about the tendency of the proposition to persist over time.


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