119 search results - page 21 / 24 » Inter-Task Action Correlation for Reinforcement Learning Tas... |
NIPS
1992
13 years 8 months ago
1992
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
NIPS
2008
13 years 9 months ago
2008
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
SMC
2007
IEEE
14 years 1 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
CEC
2003
IEEE
14 years 28 days ago
2003
IEEE
We introduce a technique that allows a real robot to execute real-time learning, in which GP and RL are integrated. In our former research, we showed the result of an experiment wi...
ESANN
2007
13 years 9 months ago
2007
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...