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Mimicking the Behaviour of Idiotypic AIS Robot Controllers Using Probabilistic Systems
 

Summary: Mimicking the Behaviour of Idiotypic AIS Robot Controllers Using
Probabilistic Systems
Amanda M. Whitbrook, Uwe Aickelin and Jonathan M. Garibaldi
Intelligent Modelling & Analysis Research Group,
School of Computer Science,
University of Nottingham, Nottingham, UK
ABSTRACT
Previous work has shown that robot navigation systems that
employ an architecture based upon the idiotypic network theory
of the immune system have an advantage over control
techniques that rely on reinforcement learning only. This is
thought to be a result of intelligent behaviour selection on the
part of the idiotypic robot. In this paper an attempt is made to
imitate idiotypic dynamics by creating controllers that use
reinforcement with a number of different probabilistic schemes
to select robot behaviour. The aims are to show that the idiotypic
system is not merely performing some kind of periodic random
behaviour selection, and to try to gain further insight into the
processes that govern the idiotypic mechanism. Trials are carried
out using simulated Pioneer robots that undertake navigation

  

Source: Aickelin, Uwe - School of Computer Science, University of Nottingham

 

Collections: Computer Technologies and Information Sciences