Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Counterfactual Regret Minimization   Counterfactual Regret Minimization (CFR) is the leading framework for solving
large imperfect-information games. It converges to an equilibrium by
iteratively traversing the game tree. In order to deal with extremely large
games, abstraction is typically applied before running CFR. The abstracted game
is solved with tabular CFR, and its solution is mapped back to the full game.
This process can be problematic because aspects of abstraction are often manual
and domain specific, abstraction algorithms may miss important strategic
nuances of the game, and there is a chicken-and-egg problem because determining
a good abstraction requires knowledge of the equilibrium of the game. This
paper introduces Deep Counterfactual Regret Minimization, a form of CFR that
obviates the need for abstraction by instead using deep neural networks to
approximate the behavior of CFR in the full game. We show that Deep CFR is
principled and achieves strong performance in large poker games. This is the
first non-tabular variant of CFR to be successful in large games.

13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess