Artificial evolution: a new path for artificial intelligence?
Recently there have been a number of proposals for the use of artificial evolution as a radically new approach to the development of control systems for autonomous robots. This paper explains the artificial evolution approach, using work at Sussex to illustrate it. The paper revolves around a case study on the concurrent evolution of control networks and visual sensor morphologies for a mobile robot. Wider intellectual issues surrounding the work are discussed, as is the use of more abstract evolutionary simulations as a new potentially useful tool in theoretical biology.
Husbands
P
P
School of Cognitive and Computing Sciences, University of Sussex, Brighton, United Kingdom. philh@cogs.susx.ac.uk
Harvey
I
I
Cliff
D
D
Miller
G
G
D001185:Artificial Intelligence; D005075:Biological Evolution; D003198:Computer Simulation; D003199:Computer Systems; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D016571:Neural Networks, Computer; D012371:Robotics; D014796:Visual Perception