Action Timing Discretization with Iterative-Refinement

Authors:
Todd W. Neller
Affiliations:
-
Venue:
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Year:
2002

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Abstract

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 驴-admissible variant of Korf's recursive best-first search (驴-RBFS), we introduce iterative-refinement 驴-admissible recursive best-first search (IR 驴-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.