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Publications about 'Minimax optimization'
Conference articles
  1. D. Ding, X. Wei, Z. Yang, Z. Wang, and M. R. Jovanovic. Provably efficient generalized Lagrangian policy optimization for safe multi-agent reinforcement learning. In 39th International Conference on Machine Learning, Baltimore, MD, 2022. Note: Submitted. Keyword(s): Multi-agent reinforcement learning, Constrained Markov games, Primal-dual policy optimization, Method of Lagrange multipliers, Minimax optimization. [bibtex-entry]


  2. D. Ding, K. Zhang, T. Basar, and M. R. Jovanovic. Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes. In Proceedings of the 2022 American Control Conference, Atlanta, GA, 2022. Note: To appear. Keyword(s): Constrained Markov decision processes, Policy gradient methods, Primal-dual algorithms, Minimax optimization. [bibtex-entry]


  3. D. Ding, K. Zhang, T. Basar, and M. R. Jovanovic. Natural policy gradient primal-dual method for constrained Markov decision processes. In Proceedings of the 34th Conference on Neural Information Processing Systems, Vancouver, Canada, 2020. Keyword(s): Constrained Markov decision processes, Policy gradient methods, Primal-dual algorithms, Minimax optimization. [bibtex-entry]



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Last modified: Tue May 3 09:45:45 2022
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