Sanmit Narvekar
Ph.D. Student
Sanmit is interested in reinforcement learning, and in machine learning in general. His current research focuses on curriculum learning -- the automated design of a sequence of tasks that enable autonomous agents to learn faster or better. Sanmit is also a member of the UT Austin Villa Standard Platform League team, where he works primarily on the vision system. In his free time, Sanmit enjoys playing soccer, running, and reading.
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning 2017
Sanmit Narvekar, Jivko Sinapov, and Peter Stone, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017.
Fast and Precise Black and White Ball Detection for RoboCup Soccer 2017
Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone, In {R}obo{C}up-2017: Robot Soccer World Cup {XXI}, 2017 (Eds.), Nagoya, Japan, July 2017.
Source Task Creation for Curriculum Learning 2016
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone, In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), Singapore, May 2016.
Learning Inter-Task Transferability in the Absence of Target Task Samples 2015
Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone, In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Currently affiliated with Learning Agents