Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Abstract
In this paper, I describe the application of genetic programming to evolve a controller for a robotic tank in a simulated environment.The purpose is to explore how genetic techniques can best be applied to produce controllers based on subsumption and behavior oriented languages such as REX. As part of my implementation, I developed TableRex, a modification of REX that can be expressed on a fixed-lengthgenome. Using a fixed subsumption architecture of TableRex modules, I evolved robots that beat some of the most competitive hand-coded adversaries.
