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GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 7 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
15 years 7 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood
GECCO
2008
Springer
121views Optimization» more  GECCO 2008»
15 years 7 months ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 7 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
15 years 6 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
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