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Book
This book covers the following topics: The biological paradigm, Threshold logic, Weighted Networks, The Perceptron, Perceptron learning, Unsupervised learning and clustering algori...
NN
2006
Springer
13 years 7 months ago
2006
Springer
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
JAIR
2007
13 years 7 months ago
2007
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
AIIA
2007
Springer
14 years 1 months ago
2007
Springer
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...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...