Incremental Deterministic Planning

We present a new planning algorithm that formulates the planning problem as a counting satisfiability problem in which the number of available solutions guides the planner deterministically to its goal. In comparison with existing planners, our approach eliminates backtracking and supports efficient incremental planners that add additional subformulas without the need to recompute solutions for previously provided subformulas. Our experimental results show that our approach is competitive with existing state-of-theart planners that formulate the planning problem as a satisfiability problem, then solve the satisfiability problem using specialized off-the-shelf satisfiability solvers such as zChaff. 1 Background Planning is one of the most studied problems in artificial intelligence. A planning problem is solved by a planner, which takes as input a description of an initial state, a goal, and the possible actions that can be performed in a given world. The output of the planner is...

• Type: Conference
• Year: 2006
• Where: SYNASC
• Authors: Stefan Andrei, Wei-Ngan Chin, Martin C. Rinard
• Keywords: Initial State, Planning Problem, Satisfiability Problem, SYNASC 2006