Several researchers have demonstrated how complex action sequences can be learned
through neuroevolution (ie, evolving neural networks with genetic algorithms). However …

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 …

In this paper we describe the evolution of a discrete-time recurrent neural network to control
a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely …

Learning plays a vital role in the development of autonomous agents. In this paper, we
explore the use of reinforcement learning to “shape” a robot to perform a predefined target …

We give an overview of evolutionary robotics research at Sussex over the last five years. We
explain and justify our distinctive approaches to (artificial) evolution, and to the nature of …

This paper discusses the feasibility of applying evolutionary methods to automatically
generating controllers for physical mobile robots. We overview the state-of-the-art in the …

This paper reviews evolutionary approaches to the automatic design of real robots exhibiting
a given behavior in a given environment. Such a methodology has been successfully …

For several years now, various researchers have endeavoured to apply artificial evolution to
the automatic design of control systems for robots. One of the major challenges they face is …

Recently, a new approach involving a form of simulated evolution has been proposed to
build autonomous robots. However, it is still not clear if this approach is adequate for real life …

An Indexed Bibliography of Genetic Algorithms: Years 1957-1993 Page 1 An Indexed
Bibliography of Genetic Algorithms: Years 1957-1993 compiled by Jarmo T. Alander …