A Practical Platform for On-Line Genetic Programming for Robotics

There is growing interest in on-line evolution forautonomous robots. On-line learningis critical to achieve high levels of autonomy in the face of dynamic environments, tasks, and other variable elements encountered in real world environments. Although a number of successes have been achieved with on-line evolution, these successes are largely limited to fairly simple learning paradigms, e.g. training small neural networks of relatively few weights and in simulated environments. The shortage of more complex learning paradigms is largely due to the limitations of affordable robotic platforms, which tend to be woefully underpowered for such applications.