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ICML
2003
IEEE
16 years 5 months ago
TD(0) Converges Provably Faster than the Residual Gradient Algorithm
In Reinforcement Learning (RL) there has been some experimental evidence that the residual gradient algorithm converges slower than the TD(0) algorithm. In this paper, we use the ...
Ralf Schoknecht, Artur Merke
ICML
2008
IEEE
16 years 5 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
15 years 11 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
152
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ICCS
2007
Springer
15 years 11 months ago
Complexity of Monte Carlo Algorithms for a Class of Integral Equations
In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the ...
Ivan Dimov, Rayna Georgieva
MP
2006
137views more  MP 2006»
15 years 5 months ago
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
Yu-Hong Dai, Roger Fletcher