@InProceedings{	  vidal:98a,
  author =	 {Jos\'{e} M. Vidal and Edmund H. Durfee},
  title =	 {The Moving Target Function Problem in Multi-Agent
                  Learning},
  booktitle =	 {Proceedings of the Third International Conference on
                  Multi-Agent Systems},
  publisher = 	 {{AAAI}/{MIT} press},
  year =	 1998,
  month =	 jul,
  pages = 	 {317--324},
  abstract =	 {We describe a framework that can be used to model
                  and predict the behavior of MASs with learning
                  agents. It uses a difference equation for
                  calculating the progression of an agent's error in
                  its decision function, thereby telling us how the
                  agent is expected to fare in the MAS. The equation
                  relies on parameters which capture the agents'
                  learning abilities (such as its change rate,
                  learning rate and retention rate) as well as
                  relevant aspects of the MAS (such as the impact that
                  agents have on each other). We validate the
                  framework with experimental results using
                  reinforcement learning agents in a market system, as
                  well as by other experimental results gathered from
                  the AI literature. },
  url =		 {http://jmvidal.cse.sc.edu/papers/icmas98/},
  googleid = 	 {jwRfKCiB5WkJ:scholar.google.com/},
  keywords = 	 {multiagent learning},
  cluster = 	 {7630647153125164175}
}