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PUBLICATIONS

AI/ML Conferences

  1. "Decentralized actor decentralized critic for multi-agent cooperative environments", Subramanian J., Seraj, R., and Mahajan, A., under preparation.

  2. "Approximate information state for partially observed systems", Subramanian J. and Mahajan A., The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Montreal, Canada, Jul 7–10, 2019.

  3. "Reinforcement learning for mean-field teams ",  Subramanian J., Seraj, R., and Mahajan, A., The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Montreal, Canada, Jul 7–10, 2019.

  4. "Reinforcement learning in stationary mean-field games", Subramanian J. and Mahajan A., International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Montreal, Canada, 13-17 May, 2019.

AI/ML Workshops

  1. "Mean-field games between teams", Subramanian J., Kumar A., and Mahajan, A., 11th Workshop on Dynamic Games in Management Science, Montreal, Canada, Oct 24–25, 2019.

  2. "Reinforcement learning for mean-field teams ",  Subramanian J., Seraj, R., and Mahajan, A., AAMAS Workshop on Adaptive and Learning Agents, Montreal Canada, 13-17 May, 2019. 

  3. "A policy gradient algorithm to compute boundedly rational stationary mean field equilibria ", Subramanian J. and Mahajan A., Proceedings of the ICML/IJCAI/AAMAS Workshop on Planning and Learning (PAL-18), Stockholm, Sweden, July 15, 2018.

Control theory Conferences

  1. "Approximate information state for partially observed systems", Subramanian J. and Mahajan A., IEEE Conference on Decision and Control (CDC), Nice, France, Dec 11–13, 2019.

  2. "Renewal Monte Carlo: Renewal theory based reinforcement learning",  Subramanian J., and Mahajan, A., IEEE Conference on Decision and Control (CDC), Miami, Florida, Dec 17–19, 2018.

  3. "On controllability of leader-follower dynamics over a directed graph", Subramanian J., Mahajan A., and Paranjape A.A., IEEE Conference on Decision and Control (CDC), Miami, Florida, Dec 17–19, 2018.

  4. "Stochastic approximation based methods for computing the optimal thresholds in remote-state estimation with packet drops", Chakravorty, J., Subramanian, J. and Mahajan, A., American Control Conference (ACC), Seattle, WA, May 24–26, 2017.

Journal Publications

  1. "Renewal Monte Carlo: Renewal theory based reinforcement learning",  Subramanian J., and Mahajan, A., submitted to IEEE Transactions on Automatic Control, 2019.

  2. "On the Link Between Weighted Least-Squares and Limiters Used in Higher-Order Reconstructions for Finite Volume Computations of Hyperbolic Equations", (with Prof. J.C. Mandal) in Applied Numerical Mathematics, 05/2008; 58(5):705-725

  3. "High Resolution Finite Volume Computations Using A Novel Weighted Least-Squares Formulation" (with Prof. J.C. Mandal and S Rao) in International Journal of Numerical Methods in Fluids, 03/2008; 56(8):1425 - 1431

Patent Applied For

  • "Graph Based Ontology Modelling System", filed in India in August, 2014

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