In recent years there have been great strides in artificial intelligence (AI), with games often
serving as challenge problems, benchmarks, and milestones for progress. Poker has served …

Despite its important applications in Machine Learning, min-max optimization of objective
functions that are nonconvex-nonconcave remains elusive. Not only are there no known first …

We show that computing approximate stationary Markov coarse correlated equilibria (CCE)
in general-sum stochastic games is PPAD-hard, even when there are two players, the game …

We give a simple and computationally efficient algorithm that, for any constant ε> 0, obtains ε
T-swap regret within only T=(n) rounds; this is an exponential improvement compared to the …

Combinatorial allocation involves assigning bundles of items to agents when the use of
money is not allowed. Course allocation is one common application of combinatorial …

In this paper, a nonlinear fractional emerging telecommunication model with higher–order
dispersive cubic–quintic is studied by using two recent computational schemes. This kind of …

Polymatrix games belong to a class of multi-player games, in which players interact
pairwisely and the underlying pairwise interactions are defined by a simple undirected …

In our recent paper [Rubinstein 2016] we rule out a PTAS for the 2-Player Nash Equilibrium
Problem. More precisely, we prove that there exists a constant ϵ> 0 such that, assuming the …

We consider the problem of decentralized multi-agent reinforcement learning in Markov
games. A fundamental question is whether there exist algorithms that, when run …

Understanding the behavior of no-regret dynamics in general N-player games is a
fundamental question in online learning and game theory. A folk result in the field states that …