Constructing Goal Agenda and Macro Actions Using Proposition Relation Graphs in Planning

Abstract

This paper focuses on graph properties of relaxed planning graph(RPG),a widely-used tool in automated planning.When proposition levels are extracted from RPG,and thus,used to build a proposition relation graph(PRG),it is found that PRG keeps primary planning properties in RPG.Preliminary research results include the following four aspects: The close pth out-neighborhoods(CON) of initial proposition set(IPS) is the relaxed reachable proposition set(R-RPS) in planning;the maximum distance from any proposition in initial state to any proposition in goal states is a reasonable estimation of the plan length;acyclic order in graph indicates that some orders that held corresponding propositions are necessary;contraction of in/out cut-vertex means construction of macro-action is currently being planned.The first and second results show PRG keeps planning properties in RPG,and the third and fourth results can be used in goal agenda building and macro-action construction.Three related algorithms are proposed: PRG in RPG finding algorithm,an O(mn2/4)(n is the number of propositions in RPG,m is the number of actions in RPG) algorithm;acyclic order reduction algorithm,an O(n+m)(n is the number of nodes in PRG,m is the number of edges in PRG) algorithm;macro action suggestion algorithm,an O(n2)(n is the number of nodes in PRG) algorithm.