Toward Evolution of Electronic Animals Using Genetic Programming
John R. Koza, Forrest H Bennett, David André, Martin A. Keane · 2004
This paper describes an automated process for designing an optimal food-foraging controller for a lizard. The controller consists of an analog electrical circuit that is evolved using the principles of natural selection, sexual recombination, and developmental biology. Genetic programming creates both the topology of the controller circuit and the numerical values for each electrical component. 1. Introduction Connectionist learning algorithms, reinforcement learning algorithms, genetic algorithms, and other learning algorithms all require, in one way or another, that the system be exposed, in its learning phase, to a non-trivial number of training cases that are representative of the environment. Researchers in the field of artificial life usually adopt one of two approaches for exposing their system to these training cases. One approach is to simulate the system inside a computer; the other approach is to operate the system in a real-world environment. An example of the first appro...