Performance of decision making: individuals and an environment

Abstract

In this paper, we focus on the procedure whereby an autonomous multiple robot system constructs feasible paths. We formulate optimal solutions in the following two cases; (i) a robot makes the decision by itself, (ii) an environment (or specific locations in an environment) gathers information and makes suggestions. We also propose learning algorithms for appropriate path construction in both cases. Then we discuss the efficiency of the two cases based on optimal solutions and learning results of simulations.