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» Parameter approximate dynamic optimization for PSO systems
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ICML
2006
IEEE
15 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
ATAL
2005
Springer
15 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
CDC
2010
IEEE
182views Control Systems» more  CDC 2010»
14 years 4 months ago
An approximate dual subgradient algorithm for multi-agent non-convex optimization
We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
Minghui Zhu, Sonia Martínez
AUTOMATICA
2008
154views more  AUTOMATICA 2008»
14 years 9 months ago
Approximately bisimilar symbolic models for nonlinear control systems
Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models ar...
Giordano Pola, Antoine Girard, Paulo Tabuada
ICRA
2010
IEEE
185views Robotics» more  ICRA 2010»
14 years 8 months ago
Camera parameters auto-adjusting technique for robust robot vision
— How to make vision system work robustly under dynamic light conditions is still a challenging research focus in computer/robot vision community. In this paper, a novel camera p...
Huimin Lu, Hui Zhang, Shaowu Yang, Zhiqiang Zheng