Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 352-361 |
| Number of pages | 10 |
| Journal | INTEGRATED CIRCUIT AND SYSTEMS DESIGN: POWER AND TIMING MODELING, OPTIMIZATION AND SIMULATION |
| Volume | 5216 |
| Publication status | Published - 2008 |
Keywords
- Cartesian Genetic Programming
- Adaptive computing
- Co-evolution of hybrid systems
- Artificial Neural Networks