Tamer Basar
25 papers · 2018–2026 · 6 venues · across top CS/AI venues
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Achievements
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(12)
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(2)
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(81)
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Top co-authors
Research topics
Reinforcement Learning
(23)
Methods
(20)
Machine Learning
(15)
Artificial Intelligence
(12)
Optimization & Theory
(12)
Core AI
(11)
Applications
(6)
Learning Types Β· Machine Learning
(6)
Mathematics & Optimization
(3)
Optimization
(3)
Deep Learning
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Keywords
multi-agent reinforcement learning
(12)
sample complexity
(7)
markov game
(7)
policy optimization
(6)
nash equilibrium
(6)
zero-sum game
(5)
reinforcement learning
(4)
policy gradient
(3)
natural policy gradient
(3)
mean field game
(3)
robust control
(3)
coarse correlated equilibrium
(3)
primal-dual method
(2)
constrained optimization
(2)
function approximation
(2)
risk-sensitive control
(2)
upper confidence bound
(2)
convergence guarantee
(2)
linear quadratic regulator
(2)
model-based reinforcement learning
(2)
Papers
Near Optimal Convergence to Coarse Correlated Equilibrium in General-Sum Markov Games
L4DC 2026
Convergence and Sample Complexity of Natural Policy Gradient Primal-Dual Methods for Constrained MDPs
JMLR 2025
OΜ(T^-1) Convergence to (coarse) correlated equilibria in full-information general-sum Markov games
L4DC 2024
Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms
L4DC 2024
Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective
L4DC 2024
A Reinforcement Learning Look at Risk-Sensitive Linear Quadratic Gaussian Control
L4DC 2023
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
JMLR 2023
Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity
NeurIPS 2023
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path
AISTATS 2023
A Mean-Field Game Approach to Cloud Resource Management with Function Approximation
NeurIPS 2022
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning
ICML 2022
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning
AAAI 2021
Decentralized Q-learning in Zero-sum Markov Games
NeurIPS 2021
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
NeurIPS 2021
Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
ICML 2021
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
NeurIPS 2020
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
NeurIPS 2020
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes
NeurIPS 2020
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems
NeurIPS 2020
Policy Optimization for H_2 Linear Control with H_β Robustness Guarantee: Implicit Regularization and Global Convergence
L4DC 2020
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
NeurIPS 2020
Robust Multi-Agent Reinforcement Learning with Model Uncertainty
NeurIPS 2020
Non-Cooperative Inverse Reinforcement Learning
NeurIPS 2019
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games
NeurIPS 2019
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
ICML 2018