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ORCIDKaushik Subramanian
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2020 – today
- 2024
[i2]Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone:
A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. CoRR abs/2406.12563 (2024)- 2022
- [j7]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:
Outracing champion Gran Turismo drivers with deep reinforcement learning. Nat. 602(7896): 223-228 (2022) - 2021
- [j6]Patrick Mannion, Anna Harutyunyan, Bei Peng, Kaushik Subramanian:
Special issue on adaptive and learning agents 2018. Knowl. Eng. Rev. 36: e7 (2021) - 2020
- [b1]Kaushik Subramanian:
Policy-based exploration for efficient reinforcement learning. Georgia Institute of Technology, Atlanta, GA, USA, 2020
2010 – 2019
- 2018
- [j5]Patrick Mannion, Anna Harutyunyan, Kaushik Subramanian:
Special issue on adaptive and learning agents 2017. Knowl. Eng. Rev. 33: e18 (2018) - [c10]David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura:
Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning. ICRA 2018: 2034-2039 - 2017
- [i1]David Isele, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura:
Navigating Intersections with Autonomous Vehicles using Deep Reinforcement Learning. CoRR abs/1705.01196 (2017) - 2016
- [c9]Kaushik Subramanian, Charles Lee Isbell Jr., Andrea Lockerd Thomaz:
Exploration from Demonstration for Interactive Reinforcement Learning. AAMAS 2016: 447-456 - [c8]Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg, Charles L. Isbell Jr., Andrea Thomaz:
Policy Shaping in Domains with Multiple Optimal Policies: (Extended Abstract). AAMAS 2016: 1455-1456 - 2014
- [j4]Luis C. Cobo, Kaushik Subramanian, Charles Lee Isbell Jr., Aaron D. Lanterman, Andrea Lockerd Thomaz:
Abstraction from demonstration for efficient reinforcement learning in high-dimensional domains. Artif. Intell. 216: 103-128 (2014) - [j3]Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias:
Economic model predictive control for inventory management in supply chains. Comput. Chem. Eng. 64: 71-80 (2014) - 2013
- [j2]Kaushik Subramanian, James B. Rawlings, Christos T. Maravelias, Jesus Flores-Cerrillo, Lawrence Megan:
Integration of control theory and scheduling methods for supply chain management. Comput. Chem. Eng. 51: 4-20 (2013) - [c7]Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz:
Policy Shaping: Integrating Human Feedback with Reinforcement Learning. NIPS 2013: 2625-2633 - 2012
- [j1]Kaushik Subramanian, Christos T. Maravelias, James B. Rawlings:
A state-space model for chemical production scheduling. Comput. Chem. Eng. 47: 97-110 (2012) - [c6]Baris Akgün, Kaushik Subramanian, Andrea Lockerd Thomaz:
Novel Interaction Strategies for Learning from Teleoperation. AAAI Fall Symposium: Robots Learning Interactively from Human Teachers 2012 - 2011
- [c5]Baris Akgün, Kaushik Subramanian, Jaeeun Shim, Andrea Lockerd Thomaz:
Learning Tasks and Skills Together From a Human Teacher. AAAI 2011: 1868-1869 - [c4]Monica Babes, Vukosi Marivate, Kaushik Subramanian, Michael L. Littman:
Apprenticeship Learning About Multiple Intentions. ICML 2011: 897-904 - 2010
- [c3]Kaushik Subramanian:
Task Space Behavior Learning for Humanoid Robots using Gaussian Mixture Models. AAAI 2010: 1961-1962 - [c2]Kaushik Subramanian, Michael L. Littman:
Efficient Apprenticeship Learning with Smart Humans. Enabling Intelligence through Middleware 2010 - [c1]Thomas J. Walsh, Kaushik Subramanian, Michael L. Littman, Carlos Diuk:
Generalizing Apprenticeship Learning across Hypothesis Classes. ICML 2010: 1119-1126
Coauthor Index
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