DOI:
Abstract:
This paper describes a line of research oriented toward building planners in the classical style but with probabilistic semantics. The BURIDAN planner uses classical planning techniques to build straight-fine plans (without feedback) that probably achieve a goal; the C-BURIDAN planner extends the representation and algorithm to handle sensing actions and conditional plans. The CL-BURIDAN planner adds the concept of a looping construct. In each case the ability to plan in uncertain domains is gained without sacrificing the essence of classical state-space operators or goal-directed backchaining algorithms.