A Constraint-Based Planner for Data Production

This paper presents a graph-based backtracking algorithm designed to support constraintbased planning in data production domains. This algorithm performs backtracking at two nested levels: the outerbacktracking following the structure of the planning graph to select planner subgoals and actions to achieve them and the inner-backtracking inside a subproblem associated with a selected action to find action parameter values. We show this algorithm works well in a planner applied t o automating data production in an ecological forecasting system. We also discuss how the idea of multi-level backtracking may improve efficiency of solving semi-structured constraint problems.