509 search results - page 9 / 102 » Compositional Models for Reinforcement Learning |
IJCNN
2008
IEEE
15 years 6 months ago
2008
IEEE
— Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural m...
100
Voted
WEBI
2009
Springer
15 years 6 months ago
2009
Springer
—In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about...
116
Voted
EWRL
2008
15 years 1 months ago
2008
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 ...
82
Voted
ICMLA
2007
15 years 1 months ago
2007
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
AIPS
2006
15 years 1 months ago
2006
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...