Probabilistic Planning with Information Gathering and Contingent Execution

Denise Draper, Steve Hanks and Daniel Weld

This paper presents a planning representation and algorithm that models informationproducing actions and constructs plans that exploit the information produced by those actions. We extend the BURIDAN [Kushmerick et al., 1993] probabilistic planning algorithm, adapting the action representation to model the behavior of imperfect sensors, and combine it with a framework for contingent action that extends the CNLP algorithm [Peot and Smith, 1992] for conditional execution. The result, C-BURIDAN, is an implemented planner that builds plans with probabilistic informationproducing actions and contingent execution.

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