Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A nearly Blackwell-optimal policy gradient method   For continuing environments, reinforcement learning methods commonly maximize
a discounted reward criterion with discount factor close to 1 in order to
approximate the steady-state reward (the gain). However, such a criterion only
considers the long-run performance, ignoring the transient behaviour. In this
work, we develop a policy gradient method that optimizes the gain, then the
bias (which indicates the transient performance and is important to capably
select from policies with equal gain). We derive expressions that enable
sampling for the gradient of the bias, and its preconditioning Fisher matrix.
We further propose an algorithm that solves the corresponding bi-level
optimization using a logarithmic barrier. Experimental results provide insights
into the fundamental mechanisms of our proposal.

29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph