Can a good learner compensate for a poor learner when paired in a coordination game? Previous work has given an example where a special learning algorithm (FMQ) is capable of doing just that when paired with a specific less capable algorithm even in games which stump the poorer algorithm when paired with itself. In this paper, we argue that this result is not general. We give a straightforward extension to the coordination game in which FMQ cannot compensate for the lesser algorithm. We also

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... vide other problematic pairings, and argue that another highquality algorithm cannot do so either.