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 ...

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 ...

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 ...

Artificial Intelligence and Life in 2030. Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram ...

Patrick MacAlpine and Peter Stone.

You may either type your answers or write them by hand, but you must have a copy with you in discussion section. In discussion section, your TA will check that you made a good effort on the problem ...

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.

Raw Data: Preprocess and transform raw data into something usable - data wrangling or data cleaning. Mapping Data for Visualization: map the clean data onto a specific visual representation. Rendering ...

Data Visualization starts with raw data that has to be preprocessed before it can be rendered. Data can be of many forms. It can be gathered from one or many sources. It could real or synthetic ...