Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multiagent Soft Q-Learning   Policy gradient methods are often applied to reinforcement learning in
continuous multiagent games. These methods perform local search in the
joint-action space, and as we show, they are susceptable to a game-theoretic
pathology known as relative overgeneralization. To resolve this issue, we
propose Multiagent Soft Q-learning, which can be seen as the analogue of
applying Q-learning to continuous controls. We compare our method to MADDPG, a
state-of-the-art approach, and show that our method achieves better
coordination in multiagent cooperative tasks, converging to better local optima
in the joint action space.

12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math