Our students and faculty are changing the world through their contributions to computing education, research, and industry. These awards received by members of the UT Computer Science community make ...

Patrick MacAlpine and Peter Stone.

Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, 10(1):1633–1685, 2009.

TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. Todd Hester and Peter Stone. Machine Learning, 90(3):385–429, 2013.

Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism. Kurt Dresner and Peter Stone. In The Third International Joint Conference on Autonomous Agents and Multiagent Systems ...

Grounded Action Transformation for Robot Learning in Simulation. Josiah Hanna and Peter Stone. @InProceedings{AAAI17-Hanna, author = {Josiah Hanna and Peter Stone}, title = {Grounded Action ...

I am an Associate Professor of Instruction in the Department of Computer Science.

In reinforcement learning (RL), a reward function that aligns exactly with a task's true performance metric is often sparse. For example, a true task metric might encode a reward of 1 upon success and ...

Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy. Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone. In Proceedings of the 13th International Conference on ...

Though computers have surpassed humans at many tasks, especially computationally intensive ones, there are many tasks for which human expertise remains necessary and/or useful. For such tasks, it is ...

Multiagent Systems: A survey from a machine learning perspective. Peter Stone and Manuela Veloso. Autonomous Robots, 8(3):345–383, July 2000. @Article(MASsurvey, Author="Peter Stone and Manuela Veloso ...

Imitation from observation (IfO) is the problem of learning directly from state-only demonstrations without having access to the demonstrator's actions.The lack of action information both ...