An approach to action planning based on simulated annealing

A number of new heuristic search methods have been developed in the field of automated planning over the last years. Enforced hill climbing (EHC) is a method that has been frequently used in several AI planning systems. This method presents a better performance compared to other methods in many planning domains, but it has some weaknesses. In this paper we investigate the use of a global search method based on simulated annealing. Preliminary results show significant results compared to algorithms based on enforced hill climbing.