The UT Programming Team consists of Trung Dang (coach) and teammates Aaryan Prakash, Mark Wen, and Dylan Smith from left to ...

We introduce a new entity typing task: given a sentence with an entity mention, the goal is to predict a set of free-form phrases (e.g. skyscraper, songwriter, or criminal) that describe appropriate ...

The UTCS Account Creation application is here - log in with your UT EID, and follow the instructions. Please note that students enrolled in the UTCS Online Master of Computer Science program are not ...

Researchers at The University of Texas at Austin and Cognizant AI Labs have developed an AI-driven system that leverages 175 years of global land use and carbon storage data to generate optimal ...

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

Transfer Learning for Reinforcement Learning on a Physical Robot. Samuel Barrett, Matt E. Taylor, and Peter Stone. In Ninth International Conference on Autonomous Agents and Multiagent Systems - ...

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 ...

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 ...

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

Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition. Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter ...

Relaxed Exploration Constrained Reinforcement Learning. Shahaf S. Shperberg, Bo Liu, and Peter Stone. @InProceedings{shahaf_shperberg_AAMAS_2024, author = {Shahaf S. Shperberg and Bo Liu and Peter ...

A critical bottleneck limiting imitation learning in robotics is the lack ofdata. This problem is more severe in mobile manipulation, where collectingdemonstrations is harder than in stationary ...