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» Building Relational World Models for Reinforcement Learning
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ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
13 years 6 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...
ACRI
2004
Springer
13 years 11 months ago
Learning What to Eat: Studying Inter-relations Between Learning, Grouping, and Environmental Conditions in an Artificial World
Abstract. In this paper we develop an artificial world model to investigate how environmental conditions affect opportunities for learning. We model grouping entities that learn wh...
Daniel J. van der Post, Paulien Hogeweg
ATAL
2008
Springer
13 years 9 months ago
Switching dynamics of multi-agent learning
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Peter Vrancx, Karl Tuyls, Ronald L. Westra
IROS
2007
IEEE
164views Robotics» more  IROS 2007»
14 years 2 months ago
Emulation and behavior understanding through shared values
— Neurophysiology has revealed the existence of mirror neurons in brain of macaque monkeys and they shows similar activities during executing an observation of goal directed move...
Yasutake Takahashi, Teruyasu Kawamata, Minoru Asad...
ECML
2005
Springer
14 years 1 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...