Why would a self-improving agent not improve its own decision-theory to reach an optimum without human intervention, given a "comfortable" utility function in the first place?

A self-improving agent does improve its own decision theory, but it uses its current decision theory to predict which self-modifications would be improvements, and broken decision theories can be wrong about that. Not all starting points converge to the same answer.