Daniel Gnad

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Recent work has introduced fork-decoupled search, addressing classical planning problems where a single center component provides preconditions for several leaf components. Given a fixed center path ⇡ C , the leaf moves compliant with ⇡C can then be scheduled independently for each leaf. Forkdecoupled search thus searches over center paths only, maintaining(More)
Star-topology decoupling is a recent search reduction method for forward state space search. The idea basically is to automatically identify a star factoring, then search only over the center component in the star, avoiding interleavings across leaf components. The framework can handle complex star topologies, yet prior work on decoupled search considered(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)