We investigate the problem of cost-optimal planning in ASP. Current ASP planners can be trivially extended to a cost-optimal one by adding weak constraints, but only for a given makespan (number of steps). It is desirable to have a planner that guarantees global optimality. In this paper, we present two approaches to addressing this problem. First, we show how to engineer a cost-optimal planner composed of two ASP programs running in parallel. Using lessons learned from this, we then develop an entirely new approach to cost-optimal planning, stepless planning, which is completely free of makespan. Experiments to compare the two approaches with the only known cost-optimal planner in SAT reveal good potentials for stepless planning in ASP. The paper is under consideration for acceptance in TPLP.
We present the first effective SAT heuristics for planning with expressive planning languages such as ADL. Recently, SAT heuristics for STRIPS planning have been introduced. In this work we show that the basic ideas in the heuristic can be generalized to actions with conditional effects but without disjunction, and that disjunction requires a more fundamental analysis of the STRIPS heuristic, which, despite complications, will still lead to a natural heuristic which can be implemented efficiently. The experimental analysis shows substantial and systematic improvements over the state of the art in planning with SAT with ADL.