A Meta-CSP Model for Optimal Planning

One approach to optimal planning is to first start with a sub- optimal solution as a seed plan, and then iteratively search for shorter plans. This approach inevitably leads to an increase in the size of the model to be solved. We introduce a reformulation of the planning problem in which the problem is described as a meta- CSP, which controls the search of an underlying SAT solver. Our results show that this approach solves a greater number of problems than both Maxplan and Blackbox, and our analysis discusses the advantages and disadvantages of searching in the backwards direction.

• Type: Conference
• Year: 2007
• Where: SARA
• Authors: Peter Gregory, Derek Long, Maria Fox
• Keywords: Artificial Intelligence, Optimal Planning, Optimal Solution, SARA 2007, Seed Plan