News

Department of Computer Science - University of Texas at Austin3d
Smarter Land Use Decisions with AI for a Sustainable Future
Researchers at The University of Texas at Austin and Cognizant AI Labs have developed an AI-driven system that leverages 175 ...
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TAMER: Training an Agent Manually via Evaluative Reinforcement
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 ...
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Overlapping Layered Learning
Patrick MacAlpine and Peter Stone.
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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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Transfer Learning for Reinforcement Learning on a Physical Robot
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 - ...
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Generative Adversarial Imitation from Observation
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 ...
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UT Austin Villa RoboCup 3D Simulation Base Code Release
UT Austin Villa RoboCup 3D Simulation Base Code Release. Patrick MacAlpine and Peter Stone. In Sven Behnke, Daniel D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup ...
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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 ...
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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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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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Relaxed Exploration Constrained Reinforcement Learning
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 ...
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N-Agent Ad Hoc Teamwork
Current approaches to learning cooperative multi-agent behaviors assumerelatively restrictive settings. In standard fully cooperative multi-agentreinforcement learning, the learning algorithm controls ...