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» Removing the Genetics from the Standard Genetic Algorithm
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AAAI
2007
15 years 6 days ago
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ACSC
2009
IEEE
15 years 4 months ago
Inference of Gene Expression Networks Using Memetic Gene Expression Programming
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
Armita Zarnegar, Peter Vamplew, Andrew Stranieri
PPSN
2004
Springer
15 years 3 months ago
Exploring the Evolutionary Details of a Feasible-Infeasible Two-Population GA
Abstract. A two-population Genetic Algorithm for constrained optimization is exercised and analyzed. One population consists of feasible candidate solutions evolving toward optimal...
Steven Orla Kimbrough, Ming Lu, David Harlan Wood
HIS
2008
14 years 11 months ago
Towards a Highly Scalable Hybrid Metaheuristic for Haplotype Inference Under Parsimony
Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This ...
Stefano Benedettini, Luca Di Gaspero, Andrea Roli
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
15 years 3 months ago
Isolating the benefits of respect
The three mechanisms of crossover are transmission, assortment, and respect. Of these three mechanisms, assortment (i.e. recombination) is traditionally viewed as the primary feat...
Stephen Chen, Gregory Pitt