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GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
13 years 7 months ago
Single step evolution of robot controllers for sequential tasks
The generation of robot controllers for a task requiring a sequence of elementary behaviors is still a challenge. If these behaviors are known, intermediate steps can be given to ...
Stéphane Doncieux, Jean-Baptiste Mouret
SAB
2010
Springer
117views Optimization» more  SAB 2010»
13 years 8 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
Sebastian Risi, Kenneth O. Stanley
WSOM
2009
Springer
14 years 4 months ago
Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas
We propose Merge Growing Neural Gas (MGNG) as a novel unsupervised growing neural network for time series analysis. MGNG combines the state-of-the-art recursive temporal context of...
Andreas Andreakis, Nicolai von Hoyningen-Huene, Mi...
IJCNN
2006
IEEE
14 years 3 months ago
Optimal Design of SVC Damping Controllers with Wide Area Measurements Using Small Population based PSO
—Static Var Compensator (SVC) are employed for providing better voltage regulation and transient stability especially for increased power transfer through the transmission lines....
Tridib K. Das, Sandhya R. Jetti, Ganesh K. Venayag...
IJON
2002
154views more  IJON 2002»
13 years 9 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec