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» Continuous Capacities on Continuous State Spaces
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AUTOMATICA
2010
96views more  AUTOMATICA 2010»
13 years 8 months ago
Issues in sampling and estimating continuous-time models with stochastic disturbances
: The standard continuous time state space model with stochastic disturbances the mathematical abstraction of continuous time white noise. To work with well defined, discrete time ...
Lennart Ljung, Adrian Wills
ICML
1996
IEEE
14 years 21 days ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
ICMLA
2004
13 years 10 months ago
Variable resolution discretization in the joint space
We present JoSTLe, an algorithm that performs value iteration on control problems with continuous actions, allowing this useful reinforcement learning technique to be applied to p...
Christopher K. Monson, David Wingate, Kevin D. Sep...
JMLR
2010
137views more  JMLR 2010»
13 years 3 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
JMLR
2006
124views more  JMLR 2006»
13 years 8 months ago
Policy Gradient in Continuous Time
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Rémi Munos