Action timing discretization with iterative-refinement

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