Action Timing Discretization with Iterative-Refinement
نویسنده
چکیده
Artificial Intelligence search algorithms search discrete systems. To apply such algorithms to continuous systems, such systems must first be discretized, i.e. approximated as discrete systems. Action-based discretization requires that both action parameters and action timing be discretized. We focus on the problem of action timing discretization. After describing an -admissible variant of Korf’s recursive best-first search ( RBFS), we introduce iterative-refinement -admissible recursive best-first search (IR -RBFS) which offers significantly better performance for initial time delays between search states over several orders of magnitude. Lack of knowledge of a good time discretization is compensated for by knowledge of a suitable solution cost upper bound.
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