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EWRL
2008
13 years 11 months ago
Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
Kirill Dyagilev, Shie Mannor, Nahum Shimkin
AR
2004
84views more  AR 2004»
13 years 10 months ago
Reinforcement learning of humanoid rhythmic walking parameters based on visual information
This paper presents a method for learning the parameters of rhythmic walking to generate purposive humanoid motions. The controller consists of the two layers: rhythmic walking is...
Masaki Ogino, Yutaka Katoh, Masahiro Aono, Minoru ...
ICSTM
2000
103views Management» more  ICSTM 2000»
13 years 11 months ago
The worst failure: repeated failure to learn
Performance measurement systems based on the principle that "if you can't measure it, you can't manage it" reinforce a short-term culture by focussing on tangi...
Alan C. McLucas
AI
1998
Springer
13 years 9 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
KESAMSTA
2007
Springer
14 years 4 months ago
Reinforcement Learning on a Futures Market Simulator
: In recent years, market forecasting by machine learning methods has been flourishing. Most existing works use a past market data set, because they assume that each trader’s in...
Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fuk...