Autonomous parallel heuristic combinatorial search

Abstract

Heuristic search is the process of searching a state space under the guidance of an evaluation function. Most research to date on parallelizing heuristic search algorithms has emphasized system problems such as load balancing and reduction in memory use. In this paper, a theoretical analysis of a new autonomous parallel heuristic search algorithm is introduced. Rather than simply dividing the search space among the processors, the processors share information that monitors the progress of the search and use consensus to limit the amount of time spent in expanding nodes that are not on the optimal path. Each processor uses a different admissible heuristic function, and it is shown that the expected number of nodes generated by each processor in the course of the search is reduced by a factor that reflects the consensus among the processors. The asynchronous behavior of the algorithm eliminates synchronization delays.