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Factored planning decouples planning tasks into subsets (factors) of state variables. The traditional focus is on handling complex cross-factor interactions. Departing from this, we introduce a form of target-profile factoring, forcing the cross-factor interactions to take the form of a fork, with several leaf factors and one potentially very large root(More)
Fork decoupling is a recent approach to exploiting problem structure in state space search. The problem is assumed to take the form of a fork, where a single (large) center component provides preconditions for several (small) leaf components. The leaves are then conditionally independent in the sense that, given a fixed center path π C , the compliant leaf(More)
Red-black planning is a recent approach to partial delete relaxation , where red variables take the relaxed semantics (accumulating their values), while black variables take the regular semantics. Practical heuristic functions can be generated from tractable sub-classes of red-black planning. Prior work has identified such sub-classes based on the black(More)
Partial delete relaxation methods, like red-black planning, are extremely powerful, allowing in principle to force relaxed plans to behave like real plans in the limit. Alas, that power has so far been chained down by the computational overhead of the use as heuristic functions, necessitating to compute a relaxed plan on every search state. For red-black(More)
Fork-decoupled search is a recent approach to classical planning that exploits fork structures, where a single center component provides preconditions for several leaf components. The decoupled states in this search consist of a center state, along with a price for every leaf state. Given this, when does one decoupled state dominate another? Such(More)
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