Making Graphplan Goal-Directed

The Graphplan algorithm exemplifies the speed-up achieveable with disjunctive representations that leverage opposing directions of refinement. It is in this spirit that we introduce Bsrgraphplan, a work in progress intended to address issues of scalability and expressiveness which are problematic for Graphplan. Specifically, we want to endow the planner with intelligent backtracking and full quantification of action schemata. Since Graphplan employs a backward chaining search, it lacks the necessary state information to support these mechanisms. We hypothesize that alternatively pointing the search in the direction of the goals provides an sufficient amelioration. Further, we demonstrate that a forward chaining search strategy can be competitive by restricting the search to the intersection of the relevant and applicable actions, and by enforcing ordering constraints on the plan prefix. The former is accomplished by using operators of a plangraph constructed in a top-down fashion to extend the plan prefix. To accomplish the latter we introduce an additional data structure, a constraint tree, which is constructed by a generalization of partial order planning.