Department of Computer Science - University of Texas at Austin

Peter Stone Delivers Keynote at the Association for the Advancement of Artificial Intelligence (AAAI) Conference

Peter Stone, Truchard Foundation Chair in Computer Science and Chair of the Department of Computer Science, presents the keynote “From How to Learn to What to Learn in Multiagent Systems and Robotics” ...
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Collecting Multilingual Parallel Video Descriptions Using Mechanical Turk

Traditional methods of collecting translation and paraphrase data can be prohibitively expensive, making construction of large, new corpora difficult. While crowdsourcing offers a cheap alternative, ...
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Transfer Learning for Reinforcement Learning Domains: A Survey

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

Hi! I'm a student at The University of Texas at Austin studying Computer Science and Mathematics.
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To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams

To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams. Peter Stone and Sarit Kraus. In The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), ...
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Deep Recurrent Q-Learning for Partially Observable MDPs

Deep Recurrent Q-Learning for Partially Observable MDPs Deep Recurrent Q-Learning for Partially Observable MDPs. Matthew Hausknecht and Peter Stone. In AAAI Fall Symposium on Sequential Decision ...
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Learning to Interpret Natural Language Commands through Human-Robot Dialog

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 ...
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Reasoning about Hypothetical Agent Behaviours and their Parameters

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 ...
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A collective AI via lifelong learning and sharing at the edge

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 ...
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Multiagent Systems: A survey from a machine learning perspective

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 ...
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CS 329E: Elements of Data Visualization - Spring 2026

Sangjun Park Email: sangjun at cs dot utexas dot edu Office Hours: Monday 11:00am – 12:00pm at GDC 1.302, TA Station Desk 5 (GDC basement) Wednesday 11:00am – 12:00pm at GDC 1.302, TA Station Desk 5 ...
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Deep Reinforcement Learning in Parameterized Action Space

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 ...