Genetic Algorithms in Robotics

Abstract

Today, contemporary computer methods inspired by biological evolution are grouped under the field called evolutionary computation. Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. The population of possible solutions evolves from one generation to the next, ultimately arriving at a satisfactory solution to the problem. These algorithms differ in the way a new population is generated from the present one, and in the way the members are represented within the algorithm. The three main elements of evolutionary computation are: 1) evolution algorithms (EA); 2) genetic programming (GP); 3) genetic algorithms (GA). Each of these three techniques mimics the processes observed in natural evolution, and provides efficient search engines by evolving populations of candidate solutions to a given problem.