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IROS
2007
IEEE
157views Robotics» more  IROS 2007»
15 years 4 months ago
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
ATAL
2005
Springer
15 years 3 months ago
Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...
Katja Verbeeck, Ann Nowé, Karl Tuyls
ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
14 years 8 months ago
Robot reinforcement learning using EEG-based reward signals
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
Iñaki Iturrate, Luis Montesano, Javier Ming...
AAAI
2006
14 years 11 months ago
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...
Yaxin Liu, Peter Stone
ECML
2005
Springer
15 years 3 months ago
Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another
We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then tra...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...