Robert P. Goldman

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We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution. We show that this clarifies several difficult issues in plan recognition including the execution of multiple interleaved root goals, partially ordered plans, and failing to observe actions. We present the PHATT(More)
In recent years there has been a growing interest among AI researchers in probabilistic and decision modelling, spurred by significant advances in representation and computation with network modelling formalisms. In applying these techniques to decision support tasks, fixed network models have proven to be inadequately expressive when a broad range of(More)
We are concerned with the implications and interactions of three common expressive extensions to classical planning: conditional plans, context-dependent actions, and nondeterministic action outcomes. All of these extensions have appeared in recent work, sometimes in conjunction, but the semantics of the combination has not been fully explored. As we have(More)
We present a semantics for interpreting probabilistic statements expressed in a first-order quantifier-free language. We show how this semantics places constraints on the probabilities which can be associated with such statements. We then consider its use in the area of story understanding. We show that for at least simple models of stories (equivalent to(More)
To be truly useful, mobile robots need to be fairly autonomous and easy to control. This is especially true in situations where multiple robots are used, due to the increase in sensory information and the fact that the robots can interfere with one another. This paper describes a system that integrates autonomous navigation, a task executive, task planning,(More)
We propose that logic (enhanced to encode probability information) is a good way of characterizing semantic interpretation. In support of this we give a fragment of an axiomatization for word-sense disambiguation, nounphrase (and verb) reference, and case disambiguation. We describe an inference engine (Frail3) which actually takes this axiomatization and(More)