Rajendran, Janarthanan

21 publications

ICLR 2025 A Generalist Hanabi Agent Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, Sarath Chandar

NeurIPS 2024 Balancing Context Length and Mixing Times for Reinforcement Learning at Scale Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar

ICLR 2024 Intelligent Switching for Reset-Free RL Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar

ICMLW 2024 Language Model-in-the-Loop: Data Optimal Approach to Recommend Actions in Text Games Arjun V Sudhakar, Prasanna Parthasarathi, Janarthanan Rajendran, Sarath Chandar

ICLR 2024 Mastering Memory Tasks with World Models Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

ICLRW 2023 Behavioral Cloning for Crystal Design Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

UAI 2023 Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran

CoLLAs 2023 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, Sarath Chandar

NeurIPSW 2023 Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

NeurIPSW 2023 Mastering Memory Tasks with World Models Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

CoLLAs 2023 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 Seijen, Sarath Chandar

CoLLAs 2023 Towards Few-Shot Coordination: Revisiting Ad-Hoc Teamplay Challenge in the Game of Hanabi Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar

NeurIPSW 2022 Replay Buffer with Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar

ICLRW 2022 Staged Independent Learning: Towards Decentralized Cooperative Multi-Agent Reinforcement Learning Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar

ICML 2022 Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm H Van Seijen

ICLRW 2022 Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen

ICML 2021 Reinforcement Learning of Implicit and Explicit Control Flow Instructions Ethan Brooks, Janarthanan Rajendran, Richard L Lewis, Satinder Singh

AAAI 2020 How Should an Agent Practice? Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

NeurIPS 2020 Meta-Learning Requires Meta-Augmentation Janarthanan Rajendran, Alexander Irpan, Eric Jang

NeurIPS 2019 Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder Singh

ICLR 2017 Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from Multiple Sources in the Same Domain Janarthanan Rajendran, Aravind S. Lakshminarayanan, Mitesh M. Khapra, P. Prasanna, Balaraman Ravindran