Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generalized conditional gradient and learning in potential mean field
  games   We apply the generalized conditional gradient algorithm to potential mean
field games and we show its well-posedeness. It turns out that this method can
be interpreted as a learning method called fictitious play. More precisely,
each step of the generalized conditional gradient method amounts to compute the
best-response of the representative agent, for a predicted value of the
coupling terms of the game. We show that for the learning sequence $\delta_k =
2/(k+2)$, the potential cost converges in $O(1/k)$, the exploitability and the
variables of the problem (distribution, congestion, price, value function and
control terms) converge in $O(1/\sqrt{k})$, for specific norms.

11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
1
The categories of this paper are: cs
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an