Model-Invariant State Abstractions for Model-based Reinforcement Learning. Manan Tomar, Amy Zhang, Roberto Calandra, Matthew E. Taylor, Joelle Pineau. Pre-print. Accepted at the SSL4RL workshop at ICLR 2021.

Mirror Descent Policy Optimization. Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh. Pre-print. Accepted as a contributed talk at the DeepRL NeurIPS 2020 workshop.

Multi-step Greedy Reinforcement Learning Algorithms. Manan Tomar*, Yonathan Efroni*, Mohammad Ghavamzadeh. Accepted at the International Conference on Machine Learning, ICML 2020.

Successor Options : An Option Discovery Algorithm for Reinforcement Learning. Manan Tomar*, Rahul Ramesh*, Balaraman Ravindran. Accepted at the International Joint Conference on Artificial Intelligence, IJCAI 2019.

MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. Manan Tomar, Akhil Sathuluri, Balaraman Ravindran. Accepted at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019.

Other Projects

Multi-Agent Reinforcement Learning using Graph Neural Networks. Rohan Saphal*, Manan Tomar*, Balaraman Ravindran. Pre-print.

A Survey on Successor Representation. Manan Tomar, Balaraman Ravindran. Pre-print.

Quantum Entanglement in Learning Representations. Ashish Kumar*, Manan Tomar*, Sutanu Chakraborti. Pre-print.