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#computer-science #machine-learning #reinforcement-learning
If an objective cannot b e learned, it does in de ed draw its utility into question. In the case of the VE , however, there is a way out. Note that the same solution, w = 1, is optimal for both MRPs above (assuming µ is the same for the two indistinguishable states in the right MRP). Is this a coincidence, or could it be generally t ru e that all MDPs with the same data distribution also have the same optimal parameter vector? If this is true—and we will show next that it is—then the VE remains a usable objective. The VE is not learnable, but the parameter that optimizes it is!
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