Kaushik Subramanian

According to our database, Kaushik Subramanian authored at least 20 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo.

Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone

CoRR, 2024

2022

Outracing champion Gran Turismo drivers with deep reinforcement learning.

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

Nat., 2022

2021

Special issue on adaptive and learning agents 2018.

Patrick Mannion, Anna Harutyunyan, Bei Peng, Kaushik Subramanian

Knowl. Eng. Rev., 2021

2020

Policy-based exploration for efficient reinforcement learning.

Kaushik Subramanian

PhD thesis, 2020

2018

Special issue on adaptive and learning agents 2017.

Patrick Mannion, Anna Harutyunyan, Kaushik Subramanian

Knowl. Eng. Rev., 2018

Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning.

David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Navigating Intersections with Autonomous Vehicles using Deep Reinforcement Learning.

David Isele, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura

CoRR, 2017

2016

Exploration from Demonstration for Interactive Reinforcement Learning.

Kaushik Subramanian, Charles Lee Isbell Jr., Andrea Lockerd Thomaz

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Policy Shaping in Domains with Multiple Optimal Policies: (Extended Abstract).

Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg, Charles L. Isbell Jr., Andrea Thomaz

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2014

Economic model predictive control for inventory management in supply chains.

Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias

Comput. Chem. Eng., 2014

Abstraction from demonstration for efficient reinforcement learning in high-dimensional domains.

Luis C. Cobo, Kaushik Subramanian, Charles Lee Isbell Jr., Aaron D. Lanterman, Andrea Lockerd Thomaz

Artif. Intell., 2014

2013

Integration of control theory and scheduling methods for supply chain management.

Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias, Jesus Flores-Cerrillo, Lawrence Megan

Comput. Chem. Eng., 2013

Policy Shaping: Integrating Human Feedback with Reinforcement Learning.

Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

A state-space model for chemical production scheduling.

Kaushik Subramanian, Christos T. Maravelias, James B. Rawlings

Comput. Chem. Eng., 2012

Novel Interaction Strategies for Learning from Teleoperation.

Baris Akgün, Kaushik Subramanian, Andrea Lockerd Thomaz

Proceedings of the Robots Learning Interactively from Human Teachers, 2012

2011

Apprenticeship Learning About Multiple Intentions.

Monica Babes, Vukosi Marivate, Kaushik Subramanian, Michael L. Littman

Proceedings of the 28th International Conference on Machine Learning, 2011

Learning Tasks and Skills Together From a Human Teacher.

Baris Akgün, Kaushik Subramanian, Jaeeun Shim, Andrea Lockerd Thomaz

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Generalizing Apprenticeship Learning across Hypothesis Classes.

Thomas J. Walsh, Kaushik Subramanian, Michael L. Littman, Carlos Diuk

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Efficient Apprenticeship Learning with Smart Humans.

Kaushik Subramanian, Michael L. Littman

Proceedings of the Enabling Intelligence through Middleware, 2010

Task Space Behavior Learning for Humanoid Robots using Gaussian Mixture Models.

Kaushik Subramanian

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010