Programmer. Hiker. Cook. Always looking for interesting problems to solve.
After performing some experiments with Q-Learning algorithm, reading tons of research papers and finally realizing that evolving walking in Aibo is a research project on its own, I decided to change the simulation to e-puck. e-puck is a differential wheels robot, kindly nicknamed “yoghurt pot” by my friends:
Why e-puck? Only two wheels to control (as opposed to 16 joints in Aibo). As a bonus, once the algorithm is completed I’ll have a chance to test it on a real robot!
The algorithm I’m implementing is Continuous Time Recurrent Neural Network (CTRNN). It’s just a first step. Second step will be to evolve two populations: agents and games. Games will represent different fitness functions, agents – neural networks. I’m back to evolutionary computation.