I am looking to use reinforcement learning to adaptively modify the weights involved in a flocking algorithm (i.e. 'boids').
Searching google revealed several libraries, but I don't know anything about any of them.
I am far from being an expert in reinforcement learning, though I have perused Sutton and Barto's classic book on the subject, so I understand some of the concepts.
A little background, in case it helps. I have a few steering behaviours (seperation, alignment, cohesion, forward, and wall avoidance), which each generate a 'force' vector and compete to tell the agent(s) where to move. Each force vector is combined in, basically, a weighted sum. I would like to 'learn' these weights adaptively so as to cause e.g. more/less clustering, reduce/increase the flock's speed, etc.
Can anyone recommend a good library to use?
I would also need some kind of linear classifier, or something, to interface the learning with the (float valued) weights for each of the flocking steering behaviours. So a library that provides a one-stop solution for this problem would be good?