Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysis and Improvement of Adversarial Training in DQN Agents With
  Adversarially-Guided Exploration (AGE)   This paper investigates the effectiveness of adversarial training in
enhancing the robustness of Deep Q-Network (DQN) policies to state-space
perturbations. We first present a formal analysis of adversarial training in
DQN agents and its performance with respect to the proportion of adversarial
perturbations to nominal observations used for training. Next, we consider the
sample-inefficiency of current adversarial training techniques, and propose a
novel Adversarially-Guided Exploration (AGE) mechanism based on a modified
hybrid of the $\epsilon$-greedy algorithm and Boltzmann exploration. We verify
the feasibility of this exploration mechanism through experimental evaluation
of its performance in comparison with the traditional decaying
$\epsilon$-greedy and parameter-space noise exploration algorithms.

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The categories of this paper are: comp-gas
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The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
2
The categories of this paper are: math