Bounded rationality in multiagent systems using decentralized metareasoning

Abstract

Metareasoning has been used as a means for achieving bounded rationality by optimizing the tradeoff between the cost and value of the decision making process. Effective monitoring techniques have been developed to allow agents to stop their computation at the "right" time so as to optimize the overall time-dependent utility of the decision. However, these methods were designed for a single decision maker. In this chapter, we analyze the problems that arise when several agents solve components of a larger problem, each using an anytime algorithm. Metareasoning is more challenging in this case because each agent is uncertain about the progress made so far by the others. We develop a formal framework for decentralized monitoring of decision making, establish the complexity of several interesting variants of the problem, and propose solution techniques for each case. © Springer-Verlag Berlin Heidelberg 2012.