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Recent Publications (From 2021)

Journal Papers

  1. A.Ramaswamy and S.Bhatnagar, Analyzing approximate value iteration algorithms, Mathematics of Operations Research, Vol.47, No.3, pp. 2138-2159, 2022 online pdf arXiv

  2. D.R.Bharadwaj, Chandramouli K., and S.Bhatnagar, A generalized minimax Q-learning algorithm for two-player zero-sum stochastic games, IEEE Transactions on Automatic Control, Vol. 67, No. 9, pp. 4816-4823, 2022 online pdf arXiv

  3. Chandramouli K., D.R.Bharadwaj, and S.Bhatnagar, Generalized Second Order Value Iteration in Markov Decision Processes, IEEE Transactions on Automatic Control, Vol. 67, Issue 8, pp. 4241-4247, 2022 online pdf arXiv

  4. P.Karmakar and S.Bhatnagar, Stochastic approximation with iterate-dependent Markov noise under verifiable conditions in compact state space with the stability of iterates not ensured, IEEE Transactions on Automatic Control, Vol.66, Issue 12, pp. 5941-5954, Dec 2021 online pdf arXiv

  5. A.Ramaswamy, S.Bhatnagar and D.Quevedo, Asynchronous stochastic approximations with asymptotically biased errors and deep multi-agent learning, IEEE Transactions on Automatic Control, Vol. 66, Issue 9, pp. 3969-3983, Sep 2021 online pdf arXiv

  6. K.J.Prabuchandran, S.Penubothula, Chandramouli K., and S.Bhatnagar, Novel first order Bayesian optimization with an application to reinforcement learning, Applied Intelligence, Springer, Vol. 51, pp. 1565-1579, 2021 online pdf

  7. P.Karmakar and S.Bhatnagar, On tight bounds for function approximation error in risk-sensitive reinforcement learning, Systems and Control Letters, Vol. 150, 104899:1-7, April 2021 online pdf

  8. A.Singla, Sindhu P.R., and S.Bhatnagar, Memory-based Deep Reinforcement Learning for Obstacle Avoidance in UAV with Limited Environment Knowledge, IEEE Transactions on Intelligent Transportation Systems, Vol.22, No.1, pp.107-118, January 2021 online pdf arXiv

Preprints Submitted to journals

Our recent papers on arXiv can be found here

Proceedings of International Conferences

  1. A.K.Jayant and S.Bhatnagar, Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm, NeurIPS 2022, New Orleans, Louisiana, USA, Nov 28 to Dec 04, 2022 arXiv

  2. R.Deb, M.Gandhi, and S.Bhatnagar, Schedule Based Temporal Difference Algorithms, 58th Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, USA, Sep 27 to 30, 2022 Online PDF (Invited Paper)

  3. Sindhu P.R., Prabuchandran K.J., S. Ganguly, and S.Bhatnagar, Data Efficient Safe Reinforcement Learning, IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, October 9-12, 2022

  4. D.R.Bharadwaj, P.Jain, Prabuchandran K.J., and S.Bhatnagar, Neural network compatible off-policy natural actor-critic algorithm, International Joint Conference on Neural Networks (IJCNN), Padova, Italy, July 18-23, 2022 arXiv (Best Student Paper Award)

  5. U.A.Mishra, S.R.Samineni, P.Goel, C.Kunjeti, H.Lodha, A.Singh, A.Sagi, S.Bhatnagar and S.Kolathaya, Dtnamic mirror descent based model predictive control for accelerating robot learning, IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, May 23-27, 2022 arXiv

  6. R.Deb and S.Bhatnagar, Gradient Temporal Difference with Momentum: Stability and Convergence, AAAI Conference on Artificial Intelligence, Vancouver, Feb 22 - Mar 01, 2022 arXiv

  7. Priya S. and S.Bhatnagar, Robust traffic signal timing control using multiagent twin delayed deep deterministic policy gradients, 14th International Conference on Agents and Artificial Intelligence (ICAART), Online, Feb 3-5, 2022

  8. P.Parnika, D.R.Bharadwaj, D.S.K.Reddy and S.Bhatnagar, Attention Actor-Critic algorithm for Multi-Agent Constrained Co-operative Reinforcement Learning, AAMAS, Virtual Event, May 3-7, 2021