88 search results - page 11 / 18 » A Framework for Reinforcement Learning on Real Robots |
IROS
2008
IEEE
14 years 1 months ago
2008
IEEE
Abstract. Both self-learning architecture (embedded structure) and explicit/implicit teaching from other agents (environmental design issue) are necessary not only for one behavior...
GECCO
2004
Springer
14 years 25 days ago
2004
Springer
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...