Using the simulated annealing algorithm for multiagent decision making

Abstract

Coordination, as a key issue in fully cooperative multiagent systems, raises a number of challenges. A crucial one among them is to efficiently find the optimal joint action in an exponential joint action space. Variable elimination offers a viable solution to this problem. Using their algorithm, each agent can choose an optimal individual action resulting in the optimal behavior for the whole agents. However, the worst-case time complexity of this algorithm grows exponentially with the number of agents. Moreover, variable elimination can only report an answer when the whole algorithm terminates. Therefore, it is unsuitable in real-time systems. In this paper, we propose an anytime algorithm, called the simulated annealing algorithm, as an approximation alternative to variable elimination. We empirically show that our algorithm can compute nearly optimal results with a small fraction of the time that variable elimination takes to find the solution to the same coordination problem. © Springer-Verlag Berlin Heidelberg 2007.