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The A2R2 Group conducts research in reinforcement learning, robotics, and autonomous agents, developing algorithms that enable intelligent systems to learn, adapt, and collaborate in complex environments. Our work spans perception, multi-agent learning, robot control, and decision-making under uncertainty, with a focus on bridging theory and real-world deployment.

TWIRL

Teaching With Interactive reinforcement Learning (TWIRL)
Reinforcement Learning has been a very useful approach, but often works slowly, because of large-scale exploration. A variant of RL, that tries to improve speed of convergence, and that has been rarely used until now is Interactive Reinforcement Learning (IRL), that is, RL is supported by a human trainer who gives some directions on how to tackle the problem.



PIs: Dr. Francisco Cruz, Prof. Dr. Stefan Wermter
Associates: Dr. Francisco Cruz, Dr. Sven Magg, Dr. Cornelius Weber
Date: July 2013 - July 2017

Publication(s) Web
Francisco Cruz, Sven Magg, Yukie Nagai, and Stefan Wermter. "Improving interactive reinforcement learning: What makes a good teacher?". Connection Science, Vol. 30, Nr. 3, pp. 306-325, March 2018.
Francisco Cruz, Sven Magg, Cornelius Weber, and Stefan Wermter. "Training Agents with Interactive Reinforcement Learning and Contextual Affordances". IEEE Transactions on Cognitive and Developmental Systems (TCDS), Vol. 8, Nr. 4, pp. 271-284, December 2016.
Francisco Cruz, German I. Parisi, Johannes Twiefel, and Stefan Wermter. "Multi-modal Integration of Dynamic Audiovisual Patterns for an Interactive Reinforcement Learning Scenario". In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 759-766, Daejeon, Korea, 2016.

TWIRL

Teaching With Interactive reinforcement Learning (TWIRL)
Reinforcement Learning has been a very useful approach, but often works slowly, because of large-scale exploration. A variant of RL, that tries to improve speed of convergence, and that has been rarely used until now is Interactive Reinforcement Learning (IRL), that is, RL is supported by a human trainer who gives some directions on how to tackle the problem.



PIs: Dr. F. Cruz, Prof. Dr. S. Wermter
Associates: F. Cruz, Dr. S. Magg, Dr. C. Weber