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» Reinforcement Learning: An Introduction
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NIPS
2008
13 years 9 months ago
Policy Search for Motor Primitives in Robotics
Many motor skills in humanoid robotics can be learned using parametrized motor primitives as done in imitation learning. However, most interesting motor learning problems are high...
Jens Kober, Jan Peters
AAAI
2006
13 years 9 months ago
Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
Vishal Soni, Satinder P. Singh
ICML
1999
IEEE
14 years 8 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 2 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,...
AIIA
2007
Springer
14 years 2 months ago
Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...