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 ...

Mina Huh, a computer science Ph.D. student at UT Austin, has been awarded a Google Ph.D. Fellowship, the company announced on ...

Transfer learning is a method where an agent reuses knowledge learned in a source task to improve learning on a target task. Recent work has shown that transfer learning can be extended to the idea of ...

E. Allen Emerson has a longstanding interest in formal methods for establishing program correctness. This was inspired in part by reading in the mid-1970's a CACM paper by Tony Hoare "Proof of Program ...

Generalizing Curricula for Reinforcement Learning. Sanmit Narvekar and Peter Stone. @InProceedings{ICML20-sanmit, author = {Sanmit Narvekar and Peter Stone}, title = {Generalizing Curricula for ...

Classically, imitation learning algorithms have been developed for idealized situations, e.g., the demonstrations are often required to be collected in the exact same environment and usually include ...

My research interests are in the area of machine learning for speech, language, and sound processing. I am particularly interested in multimodality and unsupervised ...

Artificial Intelligence and Life in 2030. Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin ...

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

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

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 ...

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