Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How memory architecture affects learning in a simple POMDP: the
  two-hypothesis testing problem   Reinforcement learning is generally difficult for partially observable Markov
decision processes (POMDPs), which occurs when the agent's observation is
partial or noisy. To seek good performance in POMDPs, one strategy is to endow
the agent with a finite memory, whose update is governed by the policy.
However, policy optimization is non-convex in that case and can lead to poor
training performance for random initialization. The performance can be
empirically improved by constraining the memory architecture, then sacrificing
optimality to facilitate training. Here we study this trade-off in a
two-hypothesis testing problem, akin to the two-arm bandit problem. We compare
two extreme cases: (i) the random access memory where any transitions between
$M$ memory states are allowed and (ii) a fixed memory where the agent can
access its last $m$ actions and rewards. For (i), the probability $q$ to play
the worst arm is known to be exponentially small in $M$ for the optimal policy.
Our main result is to show that similar performance can be reached for (ii) as
well, despite the simplicity of the memory architecture: using a conjecture on
Gray-ordered binary necklaces, we find policies for which $q$ is exponentially
small in $2^m$, i.e. $q\sim\alpha^{2^m}$ with $\alpha < 1$. In addition, we
observe empirically that training from random initialization leads to very poor
results for (i), and significantly better results for (ii) thanks to the
constraints on the memory architecture.

16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph