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IEEEPACT
2008
IEEE
13 years 12 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
GECCO
2006
Springer
174views Optimization» more  GECCO 2006»
13 years 9 months ago
Optimizing of NC tool paths for five-axis milling using evolutionary algorithms on wavelets
Computer aided NC-path generation of five-axis milling using a standard CAM-system does usually not take machine dynamics and kinematics into account. This results in machine move...
Klaus Weinert, Andreas Zabel, Heinrich Müller...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 9 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
CEC
2008
IEEE
14 years 9 hour ago
Natural Evolution Strategies
— This paper presents Natural Evolution Strategies (NES), a novel algorithm for performing real-valued ‘black box’ function optimization: optimizing an unknown objective func...
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen...
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
13 years 11 months ago
Morphing methods in evolutionary design optimization
Design optimization is a well established application field of evolutionary computation. However, standard recombination operators acting on the genotypic representation of the d...
Michael Nashvili, Markus Olhofer, Bernhard Sendhof...