@InProceedings{lee04a,
  author =	 {Chiu Fan Lee and David Wolpert},
  title =	 {Product distribution theory for control of
                  multi-agent systems},
  booktitle =	 {Proceedings of the Third International Joint
                  Conference on Autonomous Agents and MultiAgent
                  Systems},
  pages =	 {522--529},
  year =	 2004,
  publisher =	 {{ACM}},
  abstract =	 {Product Distribution (PD) theory is a new framework
                  for controlling Multi-Agent Systems (MAS s). First
                  we review one motivation of PD theory, as the
                  information-theoretic extension of conventional
                  full-rationality game theory to the case of bounded
                  rational agents. In this extension the equilibrium
                  of the game is the optimizer of a Lagrangian of the
                  (probability distribution of) the joint state of the
                  agents. Accordingly we can consider a team game
                  having a shared utility which is a performance
                  measure of the behavior of the MAS. For such a
                  scenario the game is at equilibrium the Lagrangian
                  is optimized when the joint distribution of the
                  agents optimizes the system s expected
                  performance. One common way to find that equilibrium
                  is to have each agent run a reinforcement learning
                  algorithm. Here we investigate the alternative of
                  exploiting PD theory to run gradient descent on the
                  Lagrangian. We present computer experiments
                  validating some of the predictions of PD theory for
                  how best to do that gradient descent. We also
                  demonstrate how PD theory can improve performance
                  even when we are not allowed to rerun the MAS from
                  different initial conditions, a requirement implicit
                  in some previous work.},
  keywords =     {multiagent},
  url =		 {http://jmvidal.cse.sc.edu/library/lee04a.pdf},
  comment =	 {masrg},
  googleid = 	 {KNjpYnvO9dAJ:scholar.google.com/},
  cluster = 	 {15057167958518913064}
}