4255 search results - page 115 / 851 » On Learning Boolean Functions |
NIPS
2001
14 years 11 months ago
2001
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
115
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ICML
2006
IEEE
2006
IEEE
Automatic basis function construction for approximate dynamic programming and reinforcement learning
15 years 3 months ago
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
105
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ML
2008
ACM
14 years 8 months ago
2008
ACM
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...