Mesh Based Analysis of Low Fractal Dimension Reinforcement Learning Policies
Sean Gillen,Katie Byl,Sean Gillen,Katie Byl
In previous work, using a process we call meshing, the reachable state spaces for various continuous and hybrid systems were approximated as a discrete set of states which can then be synthesized into a Markov chain. One of the applications for this approach has been to analyze locomotion policies obtained by reinforcement learning, in a step towards making empirical guarantees about the stability...
