[1] Yasin Abbasi-Yadkori and Csaba Szepesvari. Bayesian optimal control of smoothly parameterized systems: The lazy posterior sampling algorithm. arXiv preprint arXiv:1406.3926, 2014.
[2] Saghar Adler, Mehrdad Moharrami, and Vijay Subramanian. Learning a discrete set of optimal allocation rules in queueing systems with unknown service rates. arXiv preprint arXiv:2202.02419, 2022.
[3] R. Agrawal, D. Teneketzis, and V. Anantharam. Asymptotically efficient adaptive allocation schemes for controlled Markov chains: Finite parameter space. IEEE Transactions on Automatic Control, 34(12):1249-1259, 1989.
[4] Rajeev Agrawal and Demosthenis Teneketzis. Certainty equivalence control with forcing: Revisited. Systems & Control Letters, 13(5):405-412, 1989.
[5] Shipra Agrawal and Randy Jia. Optimistic posterior sampling for reinforcement learning: Worst-case regret bounds. Advances in Neural Information Processing Systems, 30, 2017.
[6] Shipra Agrawal and Randy Jia. Learning in structured MDPs with convex cost functions: Improved regret bounds for inventory management. In Proceedings of the 2019 ACM Conference on Economics and Computation, pages 743-744, 2019.
[7] Nima Akbarzadeh and Aditya Mahajan. On learning Whittle index policy for restless bandits with scalable regret. arXiv preprint arXiv:2202.03463, 2022.
[8] Nima Akbarzadeh and Aditya Mahajan. On learning Whittle index policy for restless bandits with scalable regret. IEEE Transactions on Control of Network Systems, 2023.
[9] Aristotle Arapostathis, Vivek S Borkar, Emmanuel Fernández-Gaucherand, Mrinal K Ghosh, and Steven I Marcus. Discrete-time controlled Markov processes with average cost criterion: A survey. SIAM Journal on Control and Optimization, 31(2):282-344, 1993.
[10] Peter Auer, Thomas Jaksch, and Ronald Ortner. Near-optimal regret bounds for reinforcement learning. Advances in Neural Information Processing Systems, 21, 2008.
[11] V S Borkar. The Kumar-Becker-Lin scheme revisited. Journal of Optimization Theory and Applications, 66:289–309, 1990.
[12] Rolando Cavazos-Cadena. Necessary conditions for the optimality equation in average-reward Markov decision processes. Applied Mathematics and Optimization, 19(1):97-112, 1989.
[13] Rolando Cavazos-Cadena. Weak conditions for the existence of optimal stationary policies in average Markov decision chains with unbounded costs. Kybernetika, 25(3):145-156, 1989.
[14] Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, and Sanjay Shakkottai. Job dispatching policies for queueing systems with unknown service rates. In Proceedings of the Twenty-Second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc '21, page 181–190, New York, NY, USA, 2021. Association for Computing Machinery.
[15] Sayak Ray Chowdhury, Aditya Gopalan, and Odalric-Ambrym Maillard. Reinforcement learning in parametric MDPs with exponential families. In International Conference on Artificial Intelligence and Statistics, pages 1855-1863. PMLR, 2021.
[16] Asaf Cohen, Vijay Subramanian, and Yili Zhang. Learning-based optimal admission control in a single-server queuing system. Stochastic Systems, 2024.
[17] Asaf Cohen, Vijay G. Subramanian, and Yili Zhang. Learning-based optimal admission control in a single server queuing system. https://arxiv.org/abs/2212.11316, 2022.
[18] Jim G Dai and Mark Gluzman. Queueing network controls via deep reinforcement learning. Stochastic Systems, 12(1):30-67, 2022.