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GECCO
2008
Springer
257views Optimization» more  GECCO 2008»
13 years 9 months ago
Rapid evaluation and evolution of neural models using graphics card hardware
This paper compares three common evolutionary algorithms and our modified GA, a Distributed Adaptive Genetic Algorithm (DAGA). The optimal approach is sought to adapt, in near rea...
Thomas F. Clayton, Leena N. Patel, Gareth Leng, Al...
ESOA
2006
14 years 2 days ago
Reinforcement Learning for Online Control of Evolutionary Algorithms
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). ...
A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Marti...
ICANN
2010
Springer
13 years 8 months ago
Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
Mandy Grüttner, Frank Sehnke, Tom Schaul, J&u...
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 3 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria
IISWC
2006
IEEE
14 years 2 months ago
Constructing a Non-Linear Model with Neural Networks for Workload Characterization
Workload characterization involves the understanding of the relationship between workload configurations and performance characteristics. To better assess the complexity of worklo...
Richard M. Yoo, Han Lee, Kingsum Chow, Hsien-Hsin ...