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ATAL
2007
Springer
16 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
174
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ESANN
2006
15 years 8 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...
168
Voted
IJCNN
2006
IEEE
16 years 29 days ago
High-speed Bi-directional Function Approximation using Plausible Neural Networks
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen
FMCAD
2004
Springer
16 years 10 days ago
Approximate Symbolic Model Checking for Incomplete Designs
We consider the problem of checking whether an incomplete design can still be extended to a complete design satisfying a given CTL formula and whether the property is satisfied fo...
Tobias Nopper, Christoph Scholl
MOC
2010
15 years 1 months ago
Approximation of nonlinear wave equations with nonstandard anisotropic growth conditions
Weak solutions for nonlinear wave equations involving the p(x)-Laplacian, for p : (1, ) are constructed as appropriate limits of solutions of an implicit finite element discretiz...
Jonas Haehnle, Andreas Prohl