Kaushik Subramanian

30 papers A* 8A 2Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Out-of-Distribution Generalization with a SPARC: Racing 100 Unseen Vehicles with a Single Policy. AAAI Bram Grooten, Patrick MacAlpine, Kaushik Subramanian, Peter Stone, Peter R. Wurman
2026	J	`jnl`	The Trajectory Alignment Coefficient in Two Acts: From Reward Tuning to Reward Learning. CoRR Calarina Muslimani, Yunshu Du, Kenta Kawamoto, Kaushik Subramanian, Peter Stone, Peter R. Wurman
2025	J	`jnl`	A Champion-Level Vision-Based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7. IEEE Robotics Autom. Lett. Hojoon Lee, Takuma Seno, Jun Jet Tai, Kaushik Subramanian, Kenta Kawamoto, Peter Stone, Peter R. Wurman
2025	J	`jnl`	A Champion-level Vision-based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7. CoRR Hojoon Lee, Takuma Seno, Jun Jet Tai, Kaushik Subramanian, Kenta Kawamoto, Peter Stone, Peter R. Wurman
2025	J	`jnl`	Automated Reward Design for Gran Turismo. CoRR Michel Ma, Takuma Seno, Kaushik Subramanian, Peter R. Wurman, Peter Stone, Craig Sherstan
2025	J	`jnl`	Out-of-Distribution Generalization with a SPARC: Racing 100 Unseen Vehicles with a Single Policy. CoRR Bram Grooten, Patrick MacAlpine, Kaushik Subramanian, Peter Stone, Peter R. Wurman
2025	A*	`conf`	SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. ICLR Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno
2024	J	`jnl`	A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. RLJ Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone
2024	J	`jnl`	A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. CoRR Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone
2024	A*	`conf`	Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration. NeurIPS Borja G. León, Francesco Riccio, Kaushik Subramanian, Peter R. Wurman, Peter Stone
2024	J	`jnl`	SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. CoRR Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno
2022	J	`jnl`	Outracing champion Gran Turismo drivers with deep reinforcement learning. Nat. Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Raj Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano
2021	J	`jnl`	Special issue on adaptive and learning agents 2018. Knowl. Eng. Rev. Patrick Mannion, Anna Harutyunyan, Bei Peng, Kaushik Subramanian
2020	—	`—`	Policy-based exploration for efficient reinforcement learning. Kaushik Subramanian
2018	A*	`conf`	Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning. ICRA David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura
2018	J	`jnl`	Special issue on adaptive and learning agents 2017. Knowl. Eng. Rev. Patrick Mannion, Anna Harutyunyan, Kaushik Subramanian
2017	J	`jnl`	Navigating Intersections with Autonomous Vehicles using Deep Reinforcement Learning. CoRR David Isele, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura
2016	A	`conf`	Exploration from Demonstration for Interactive Reinforcement Learning. AAMAS Kaushik Subramanian, Charles Lee Isbell Jr., Andrea Lockerd Thomaz
2016	A	`conf`	Policy Shaping in Domains with Multiple Optimal Policies: (Extended Abstract). AAMAS Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg, Charles L. Isbell Jr., Andrea Thomaz
2014	J	`jnl`	Abstraction from demonstration for efficient reinforcement learning in high-dimensional domains. Artif. Intell. Luis C. Cobo, Kaushik Subramanian, Charles Lee Isbell Jr., Aaron D. Lanterman, Andrea Lockerd Thomaz
2014	J	`jnl`	Economic model predictive control for inventory management in supply chains. Comput. Chem. Eng. Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias
2013	J	`jnl`	Integration of control theory and scheduling methods for supply chain management. Comput. Chem. Eng. Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias, Jesus Flores-Cerrillo, Lawrence Megan
2013	—	`conf`	Policy Shaping: Integrating Human Feedback with Reinforcement Learning. NIPS Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz
2012	J	`jnl`	A state-space model for chemical production scheduling. Comput. Chem. Eng. Kaushik Subramanian, Christos T. Maravelias, James B. Rawlings
2012	—	`conf`	Novel Interaction Strategies for Learning from Teleoperation. AAAI Fall Symposium: Robots Learning Interactively from Human Teachers Baris Akgün, Kaushik Subramanian, Andrea Lockerd Thomaz
2011	A*	`conf`	Apprenticeship Learning About Multiple Intentions. ICML Monica Babes, Vukosi Marivate, Kaushik Subramanian, Michael L. Littman
2011	A*	`conf`	Learning Tasks and Skills Together From a Human Teacher. AAAI Baris Akgün, Kaushik Subramanian, Jaeeun Shim, Andrea Lockerd Thomaz
2010	—	`conf`	Efficient Apprenticeship Learning with Smart Humans. Enabling Intelligence through Middleware Kaushik Subramanian, Michael L. Littman
2010	A*	`conf`	Generalizing Apprenticeship Learning across Hypothesis Classes. ICML Thomas J. Walsh, Kaushik Subramanian, Michael L. Littman, Carlos Diuk
2010	A*	`conf`	Task Space Behavior Learning for Humanoid Robots using Gaussian Mixture Models. AAAI Kaushik Subramanian