An Algorithm for Probabilistic Least-Commitment Planning

We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, and actions whose eects depend on the execution-time state of the world and on random chance. Adopting a probabilistic model complicates the denition of plan success: instead of demanding a plan that provably achieves the goal, we seek plans whose probability of success exceeds the threshold. This paper describes a probabilistic semantics for planning under uncertainty, and presents a fully implemented algorithm that generates plans that succeed with probability no less than a user-supplied probability threshold. The algorithm is sound (if it terminates then the generated plan is suciently likely to achieve the goal) and complete (the algorithm will generate a solution if one exists).

• Type: Conference
• Year: 1994
• Where: AAAI
• Authors: Nicholas Kushmerick, Steve Hanks, Daniel S. Weld
• Keywords: AAAI 1994, Intelligent Agents, Probabilistic Planning Problem, Probability Threshold, User-supplied Probability Threshold