This paper presents a method for co-evolving neuro-inspired developmental programs for playing checkers. Each player's program is represented by seven chromosomes encoding digital circuits, using a form of genetic programming, called Cartesian Genetic Programming (CGP). The neural network that occurs by running the genetic programs has a highly dynamic morphology in which neurons grow, and die, and neurite branches together with synaptic connections form and change in response to situations encountered on the checkers board. The results show that, after a number of generations, by playing each other the agents play much better than those from earlier generations. Such learning abilities are encoded at a genetic level rather than at the phenotype level of neural connections. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Khan, G. M., Miller, J. F., & Halliday, D. M. (2008). Coevolution of neuro-developmental programs that play checkers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5216 LNCS, pp. 352–361). Springer Verlag. https://doi.org/10.1007/978-3-540-85857-7_31
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