Journal article

Subgoaling techniques for satisficing and optimal numeric planning

E Scala, P Haslum, S Thiébaux, M Ramirez

Journal of Artificial Intelligence Research | AI Access Foundation | Published : 2020


This paper studies novel subgoaling relaxations for automated planning with propositional and numeric state variables. Subgoaling relaxations address one source of complexity of the planning problem: the requirement to satisfy conditions simultaneously. The core idea is to relax this requirement by recursively decomposing conditions into atomic subgoals that are considered in isolation. Such relaxations are typically used for pruning, or as the basis for computing admissible or inadmissible heuristic estimates to guide optimal or satisficing heuristic search planners. In the last decade or so, the subgoaling principle has underpinned the design of an abundance of relaxation-based heuristics ..

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Awarded by Australian Research Council

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