In each iteration, SetA*: 1) pops the set with highest priority, 2) computes its next states, and 3) partitions the next states into child sets with unique and ...
In this paper we combine the goal directed search of A* with the ability of BDDs to traverse an exponential number of states in polynomial time.
In this paper we combine the goal directed search of A* with the ability of BDDs to traverse an exponential number of states in polynomial time. We introduce a ...
In this paper we combine the goal directed search of A* with the ability of BDDs to traverse an exponential number of states in polynomial time.
In this paper we combine the goal directed search of A* with the ability of BDDs to traverse an exponential number of states in polynomial time.
Abstract. In this paper we combine the goal directed search of. A* with the ability of BDDs to traverse an exponen- tial number of states in polynomial time ...
Abstract. In this paper we combine the goal directed search of. A* with the ability of BDDs to traverse an exponen- tial number of states in polynomial time ...
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In this paper we combine the goal directed search of A* with the ability of BDDs to traverse an exponential number of states in polynomial time.
In this article, we present a framework called state-set branching that combines symbolic search based on reduced ordered Binary Decision Diagrams (BDDs) ...
This work introduces a new algorithm, BDDRPA*, which is an efficient BDD-based incremental heuristic search algorithm for replanning, which outperforms ...