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ICML
2009
IEEE
15 years 10 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
CCE
2005
14 years 9 months ago
Logic-based outer approximation for globally optimal synthesis of process networks
Process network problems can be formulated as Generalized Disjunctive Programs where a logicbased representation is used to deal with the discrete and continuous decisions. A new ...
María Lorena Bergamini, Pío A. Aguir...
MOC
2010
14 years 4 months ago
A direct coupling of local discontinuous Galerkin and boundary element methods
The coupling of local discontinuous Galerkin (LDG) and boundary element methods (BEM), which has been developed recently to solve linear and nonlinear exterior transmission proble...
Gabriel N. Gatica, Norbert Heuer, Francisco-Javier...
CVPR
2003
IEEE
15 years 11 months ago
Nonparametric Belief Propagation
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
AAAI
1994
14 years 11 months ago
Learning to Explore and Build Maps
Using the methods demonstrated in this paper, a robot with an unknown sensorimotor system can learn sets of features and behaviors adequate to explore a continuous environment and...
David Pierce, Benjamin Kuipers