In this paper we study $m$-discount optimality (m ≥ -1) and
Blackwell optimality for a general class of controlled (Markov)
diffusion processes. To this end, a key step is to express the
expected discounted reward function as a Laurent series, and then
search certain control policies that lexicographically maximize the
$m$th coefficient of this series for m = -1,0,1,.... This
approach naturally leads to m-discount optimality and it gives
Blackwell optimality in the limit as m → ∞.
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