UNIVERSITY OF HERTFORDSHIRE

   COMPUTER SCIENCE RESEARCH COLLOQUIUM


		presents

 "Social Learning in a Multi-Agent System"

		speaker:

            Dr. Jason Noble 
  School of Computing, University of Leeds


	 11 February 2004 (Wednesday)

	  Lecture Theatre LC108 
      Hatfield College Lane Campus
             3:00 - 4:00 pm


 Refreshments and biscuits will be available.


      Everyone is Welcome to Attend



Abstract;
In a persistent multi-agent system, it should be possible for new
agents to benefit from the accumulated learning of more experienced
agents.  Parallel reasoning can be applied to the case of newborn
animals, and thus the biological literature on social learning may aid
in the construction of effective multi-agent systems.  Biologists have
looked at both the functions of social learning and the mechanisms
that enable it.  Many researchers have focused on the cognitively
complex mechanism of imitation; we will also consider a range of
simpler mechanisms that could more easily be implemented in robotic or
software agents.  Research in artificial life shows that complex
global phenomena can arise from simple local rules.  Similarly,
complex information sharing at the system level may result from quite
simple individual learning rules.  We demonstrate in simulation that
simple mechanisms can outperform imitation in a multi-agent system,
and that the effectiveness of any social learning strategy will depend
on the agents' environment.  Our simple mechanisms have obvious
advantages in terms of robustness and design costs.

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