arXiv research

Proves minimax sample complexity for turn-based stochastic games.

A RL approach finds Nash equilibrium for turn-based zero-sum games.

We prove the existence of Kahler-Einstein metric on a K-stable Fano manifold using the recent compactness result on Kahler-Ricci flows. The key ingredient is an algebro-geometric description of the asymptotic behavior of Kahler-Ricci flow on Fano manifolds. This is in turn based on a general finite dimensional discussi…

Combinatorial two-player games have recently been applied to knot theory. Examples of this include the Knotting-Unknotting Game and the Region Unknotting Game, both of which are played on knot shadows. These are turn-based games played by two players, where each player has a separate goal to achieve in order to win the…

Study human-machine interaction with private info using offline RL.

Recent work in reinforcement learning demonstrated that learning solely through self-play is not only possible, but could also result in novel strategies that humans never would have thought of. However, optimization methods cast as a game between two players require careful tuning to prevent suboptimal results. Hence,…

AEC Games model represents software MARL environments better than POSGs.

New assumptions and algorithm solve offline two-player zero-sum Markov games.

The paper analyzes Q-learning in 2-player Markov games and provides gap-dependent logarithmic regret bounds.

In this paper, we settle the sampling complexity of solving discounted two-player turn-based zero-sum stochastic games up to polylogarithmic factors. Given a stochastic game with discount factor $γ\in(0,1)$ we provide an algorithm that computes an $ε$-optimal strategy with high-probability given $\tilde{O}((1 - γ)^{-3}…

Study partial derivatives on non-smooth metric measure structures.

WEEND uses a neural network to recognize speech and assign speakers to words.

Recent progress in artificial intelligence through reinforcement learning (RL) has shown great success on increasingly complex single-agent environments and two-player turn-based games. However, the real-world contains multiple agents, each learning and acting independently to cooperate and compete with other agents, a…

Simpler algorithms for morphing planar and toroidal graphs.

Despite the improved accuracy of deep neural networks, the discovery of adversarial examples has raised serious safety concerns. In this paper, we study two variants of pointwise robustness, the maximum safe radius problem, which for a given input sample computes the minimum distance to an adversarial example, and the …

Efficient reinforcement learning for simultaneous-move zero-sum games using optimistic value iteration.

AppStreamer reduces mobile game storage by predicting needed files.