Publications by Janarthanan Rajendran

Activity

An Introduction to Lifelong Supervised Learning
Shagun Sodhani, Mojtaba Farmazi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed Abdelsalam, Janarthanan Rajendran, and Sarath Chandar
In ArXiv, 2022.
#DL
[arXiv]

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, and Sarath Chandar
Neural Information Processing Systems (NeurIPS), 2024.
#RL
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer
Rached Bouchoucha, Ahmed Haj Yahmed, Darshan Patil, Janarthanan Rajendran, Amin Nikanjam, Sarath Chandar, and Foutse Khomh
International Conference on Software Maintenance and Evolution (ICSME), 2024.
#RL
Mastering Memory Tasks with World Models
Mohammad Reza Samsami*, Artem Zholus*, Janarthanan Rajendran, and Sarath Chandar
International Conference on Learning Representations (ICLR), 2024. [Oral presentation.]
#RL, #DL
[openreview]
Intelligent Switching for Reset-Free RL
Darshan Patil, Janarthanan Rajendran, Glen Berseth, and Sarath Chandar
International Conference on Learning Representations (ICLR), 2024.
#RL
[openreview]
Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning
Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, and Sarath Chandar
Digital Discovery Journal, 2024.
#RL
[openreview]

Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning
Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, and Sarath Chandar
Conference on Lifelong Learning Agents (CoLLAs), 2023.
[Deep Reinforcement Learning Workshop, NeurIPS, 2022]
#RL
[arXiv]
Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi
Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, and Sarath Chandar
Conference on Lifelong Learning Agents (CoLLAs), 2023.
#RL
[paper]
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, and Sarath Chandar
Conference on Lifelong Learning Agents (CoLLAs), 2023.
#RL
[arXiv]
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, and Janarthanan Rajendran
Conference on Uncertainty in Artificial Intelligence (UAI), 2023.
#RL
[arXiv]

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan*, Ali Rahimi-Kalahroudi*, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, and Harm van Seijen
International Conference on Machine Learning (ICML), 2022.
#RL
[arXiv], [code]