In this academy, you’ll explore how data scientists analyze real-world data to uncover meaningful insights. Through hands-on projects, you’ll learn the fundamentals of data analysis and machine ...

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.

Recent work has shown that deep neural networks are capable ofapproximating both value functions and policies in reinforcementlearning domains featuring continuous state and actionspaces. However, to ...

Reasoning about Hypothetical Agent Behaviours and their Parameters. Stefano Albrecht and Peter Stone. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems ...

One vision of a future artificial intelligence (AI) is where many separate unitscan learn independently over a lifetime and share their knowledge with eachother. The synergy between lifelong learning ...

Mingyuan Zhou joined The University of Texas at Austin faculty in 2013 as an assistant professor. He has served as the 2018–2019 treasurer of the Bayesian Nonparametrics Section of the International ...

Amy Zhang is an assistant professor and Texas Instruments/Kilby Fellow in the Department of Electrical and Computer Engineering at UT Austin starting Spring 2023 and an affiliate member of the Texas ...

David Soloveichik is an Associate Professor and holds the Temple Foundation Endowed Faculty Fellowship No.4 in the Chandra Family Department of Electrical & Computer Engineering at The University of ...

Learning to Interpret Natural Language Commands through Human-Robot Dialog. Jesse Thomason, Shiqi Zhang, Raymond Mooney, and Peter Stone. In Proceedings of the 2015 International Joint Conference on ...

1/12 & 1/14 Introduction & PHY Layer Fundamentals (pdf) ...