hi, ive done experiments with neural networks before involving simulation. I have been looking for a way for a robot to learn whilst it is acting and improve itself, possibly adapting to slight environmental changes.
I think this is called real time learning.
are there any ways this can be done, aside from just letting the robot fail loads of times like you would in a simulator with a genetic algorithm or particle swarm optimisation, because that could take a while?