Department of Computer Science - University of Texas at Austin

Longhorn Developers: From Discord Server to Campus Institution

Since formalizing as a student organization, Longhorn Developers has grown to a Discord community of roughly 900 members and ...
Department of Computer Science - University of Texas at Austin

UT Computer Science Wins DOE Genesis Mission Award to Bring Autonomous Robotics to Scientific Research

Volkan Isler, professor in the Department of Computer Science and a core faculty member of Texas Robotics is leading SAFE-BOLT (Safety-Assured Force-Aware Execution for Bimanual Operations on Lab ...
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Deep Recurrent Q-Learning for Partially Observable MDPs

BibTeX Entry @InProceedings {SDMIA15-Hausknecht, author = {Matthew Hausknecht and Peter Stone}, title = {Deep Recurrent Q-Learning for Partially Observable MDPs}, booktitle = {AAAI Fall Symposium on ...
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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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Telemoma: A Modular and Versatile Teleoperation System for Mobile Manipulation

A critical bottleneck limiting imitation learning in robotics is the lack of data. This problem is more severe in mobile manipulation, where collecting demonstrations is harder than in stationary ...
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CS354P - Game Programming Paradigms

This course explores game programming paradigms in C++ using the Unreal Engine. This includes understanding and mastering event-driven, component-oriented and object-oriented programming, as well as ...
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CS 104c: Competitive Programming

Fall 2026: 54640 (20) 24 Aug - 7 Dec 2026 M 4 pm: RLP 0.128 https://gitlab.com/gpdowning-ut/cs104c/ https://www.cs.utexas.edu/~utpc/ ...
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Boosting for Regression Transfer

David Pardoe and Peter Stone.
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DARPA Urban Challenge Technical Report: Austin Robot Technology

Austin Robot Technology's (ART's) entry in the DARPA Urban Challenge has two main goals. First and foremost,the team aims to create a fully autonomous vehicle that is capable of safely and robustly ...
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Deep Reinforcement Learning in Parameterized Action Space

Recent work has shown that deep neural networks are capable of approximating both value functions and policies in reinforcement learning domains featuring continuous state and action spaces. However, ...
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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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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 ...