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» Comparative analysis of genetic algorithm implementations
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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
BMCBI
2008
214views more  BMCBI 2008»
13 years 6 months ago
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Jukka Corander, Pekka Marttinen, Jukka Siré...
NC
1998
138views Neural Networks» more  NC 1998»
13 years 8 months ago
Parallel Adaptive Genetic Algorithm
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
Leo Budin, Marin Golub, Domagoj Jakobovic
CEC
2010
IEEE
13 years 8 months ago
Global search for occlusion minimisation in virtual camera control
Abstract-- This paper presents a fast and reliable globalsearch approach to the problem of virtual camera positioning when multiple objects that need to be within the reach of the ...
Paolo Burelli, Georgios N. Yannakakis
ICPR
2006
IEEE
14 years 8 months ago
Comparative Analysis of Decision-level Fusion Algorithms for 3D Face Recognition
3D shape-based face recognition algorithms can be improved by using decision-level fusion algorithms. In this work, we present a comparative analysis of various fusion algorithms,...
Berk Gökberk, Lale Akarun