Competition, Coevolution and the Game of Tag

Tag is a children’s game based on symmetrical pursuit and evasion. In the experiments described here, control programs for mobile agents (simulated vehicles) are evolved based on their skill at the game of tag. A player’s fitness is determined by how well it performs when placed in competition with several opponents chosen randomly from the coevolving population of players. In the beginning, the quality of play is very poor. Then slightly better strategies begin to exploit the weaknesses of others. Through evolution, guided by competitive fitness, increasingly better strategies emerge over time.

[1]  Craig W. Reynolds.  Evolution of obstacle avoidance behavior: using noise to promote robust solutions , 1994 .

[2]  Antony W Merz,et al.  The Homicidal Chauffeur - A Differential Game , 1971 .

[3]  Craig W. Reynolds.  Evolution of corridor following behavior in a noisy world , 1994 .

[4]  Thomas S. Ray,et al.  An Approach to the Synthesis of Life , 1991 .

[5]  Peter J. Angeline,et al.  Competitive Environments Evolve Better Solutions for Complex Tasks , 1993, ICGA.

[6]  Una-May O'Reilly,et al.  Genetic Programming II: Automatic Discovery of Reusable Programs. , 1994, Artificial Life.

[7]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[8]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[9]  Karl Sims,et al.  Evolving 3D Morphology and Behavior by Competition , 1994, Artificial Life.

[10]  Gilbert Syswerda,et al.  A Study of Reproduction in Generational and Steady State Genetic Algorithms , 1990, FOGA.

[11]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

[12]  Ronald C. Arkin,et al.  Motor schema based navigation for a mobile robot: An approach to programming by behavior , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[13]  Kristian Lindgren,et al.  Evolutionary phenomena in simple dynamics , 1992 .

[14]  Rufus Isaacs,et al.  Differential Games , 1965 .

[15]  John R. Koza,et al.  Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex adaptive systems.

[16]  V. Braitenberg.  Vehicles, Experiments in Synthetic Psychology , 1984 .

[17]  Craig W. Reynolds.  An Evolved, Vision-Based Model of Obstacle Avoidance Behavior , 1994 .

[18]  Joe Marks,et al.  Spacetime constraints revisited , 1993, SIGGRAPH.

[19]  W. Daniel Hillis,et al.  Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .

[20]  Patrik D'haeseleer,et al.  Effects of locality in individual and population evolution , 1994 .

[21]  J. K. Kinnear,et al.  Alternatives in automatic function definition: a comparison of performance , 1994 .

[22]  Michael G. Dyer,et al.  Evolution of herding behavior in artificial animals , 1993 .