In this paper, we describe our enhancements incorporated in SGPlan (hereafter called SGPLan5) for supporting the new features of the PDDL3.0 language used in the Fifth International Planning Competition (IPC5). Based on the architecture of SGPlan that competed in the Fourth IPC (hereafter called SGPLan4), SGPLan5 partitions a large planning problem into subproblems, each with its own subgoal, and resolves those inconsistent solutions using our extended saddle-point condition. Subgoal partitioning is effective for solving large planning problems because each partitioned subproblem involves a substantially smaller search space than that of the original problem. In SGPLan5, we generalize subgoal partitioning so that the goal state of a subproblem is no longer one goal fact as in SGPLan4, but can be any fact with loosely coupled constraints with other subproblems. We have further developed methods for representing a planning problem in a multi-valued form in order to accommodate the new features in PDDL3.0, and for carrying out partitioning in the transformed space. The multi-valued representation leads to more effective heuristics for resolving goal preferences and trajectory and temporal constraints.
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