Why not use max(returns) instead of average(returns) in off-policy Monte Carlo control?
Monte Carlo methods can be incremental in an episode-by-episode sense, but not in a step-by-step (online) sense. The term Monte Carlo is often used more broadly for any estimation method whose operation involves a significant random component. It is used specically for methods based on averaging complete returns.

An obvious way to estimate it from experience, then, is simply to average the
returns observed after visits to that state. As more returns are observed, the average should converge
to the expected value. This idea underlies all Monte Carlo methods.