Kernel Mean Embedding Topology: Weak and Strong Forms for Stochastic Kernels and Implications for Model Learning.

Quantum Markov Decision Processes: General Theory, Approximations, and Classes of Policies.

Nash Equilibria for Exchangeable Team-Against-Team Games, Their Mean-Field Limit, and the Role of Common Randomness.

Existence of ε-Nash Equilibria in Nonzero-Sum Borel Stochastic Games and Equilibria of Quantized Models.

Best Ergodic Averages via Optimal Graph Filters in Reversible Markov Chains.

Quantum Markov Decision Processes Part II: Optimal Solutions and Algorithms.

Quantum Markov Decision Processes Part I: General Theory, Approximations, and Classes of Policies.

Maximum Causal Entropy Inverse Reinforcement Learning for Mean-Field Games.

Partially Observed Discrete-Time Risk-Sensitive Mean Field Games.

Optimality of Independently Randomized Symmetric Policies for Exchangeable Stochastic Teams with Infinitely Many Decision Makers.

Q-Learning in Regularized Mean-field Games.

Q-Learning for MDPs with General Spaces: Convergence and Near Optimality via Quantization under Weak Continuity.

Learning Mean-Field Games with Discounted and Average Costs.

Robustness and Approximation of Discrete-time Mean-field Games under Discounted Cost Criterion.

Common Information Approach for Static Team Problems with Polish Spaces and Existence of Optimal Policies.

Linear Mean-Field Games with Discounted Cost.

Large deviations principle for discrete-time mean-field games.

Regularized stochastic team problems.

Asymptotic Optimality of Finite Model Approximations for Partially Observed Markov Decision Processes With Discounted Cost.

A Topology for Team Policies and Existence of Optimal Team Policies in Stochastic Team Theory.

Value iteration algorithm for mean-field games.

Approximate Markov-Nash Equilibria for Discrete-Time Risk-Sensitive Mean-Field Games.

Finite-State Approximations to Discounted and Average Cost Constrained Markov Decision Processes.

Weak Feller property of non-linear filters.

Approximate Nash Equilibria in Partially Observed Stochastic Games with Mean-Field Interactions.

Fitted Q-Learning in Mean-field Games.

Discrete-time average-cost mean-field games on Polish spaces.

Markov-Nash Equilibria in Mean-Field Games with Discounted Cost.

Discrete-time Risk-sensitive Mean-field Games.

Finite Model Approximations and Asymptotic Optimality of Quantized Policies in Decentralized Stochastic Control.

Convex Analysis in Decentralized Stochastic Control, Strategic Measures, and Optimal Solutions.

On the Asymptotic Optimality of Finite Approximations to Markov Decision Processes with Borel Spaces.

Finite Model Approximations for Partially Observed Markov Decision Processes with Discounted Cost.

Output Constrained Lossy Source Coding With Limited Common Randomness.

Randomized Quantization and Source Coding With Constrained Output Distribution.

Asymptotic Optimality and Rates of Convergence of Quantized Stationary Policies in Stochastic Control.

Asymptotic Optimality of Finite Approximations to Markov Decision Processes with General State and Action Spaces.

Quantized Stationary Control Policies in Markov Decision Processes.