I’m not sure how comparable adaptive control theory notions are to “reinforcement learning”. Adaptive obviously isn’t a perfectly defined word — but your usage makes me think you might be pondering applying RL to non-stationary environments which I’m not sure is something RL would currently be necessarily likely to perform well for - many reinforcement learning techniques _do_ require (or at least perform much better) when the environment is approximately stationary — of course it can be stochastic but the distributions should be mostly fixed or else convergence challenges are likely to be exacerbated.