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Abstract: This paper summarizes recent research on competition-based learning procedures performed by the Navy Center for Applied Research in Artificial Intelligence at the Naval Research Laboratory. We have focused on a particularly interesting class of competition-based techniques called genetic algorithms. Genetic algorithms are adaptive search algorithms based on principles derived from the mechanisms of biological evolution. Recent results on the analysis of the implicit parallelism of alternative... (Update)
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BibTeX entry: (Update)
John J. Grefenstette, Kenneth A. De Jong, and William M. Spears. Competition-based learning. In Alan Meyrowitz and Susan Chipman, editors, Foundations of Knowledge Acquisition: Machine Learning, page ? Kluwer, 1992. y(Spears) ga:DeJong92h. http://citeseer.ist.psu.edu/grefenstette92competitionbased.html More
@misc{ grefenstette92competitionbased,
author = "J. Grefenstette and K. De Jong and W. Spears",
title = "Competition-based learning",
text = "John J. Grefenstette, Kenneth A. De Jong, and William M. Spears. Competition-based
learning. In Alan Meyrowitz and Susan Chipman, editors, Foundations of Knowledge
Acquisition: Machine Learning, page ? Kluwer, 1992. y(Spears) ga:DeJong92h.",
year = "1992",
url = "citeseer.ist.psu.edu/grefenstette92competitionbased.html" }
Citations (may not include all citations):2138 Genetic algorithms in search (context) - Goldberg - 1989
1931 Adaptation in natural and artificial systems (context) - Holland - 1975
275 Uniform crossover in genetic algorithms (context) - Syswerda - 1989
154 Optimization of control parameters for genetic algorithms (context) - Grefenstette - 1986
114 Reducing bias and inefficiency in the selection algorithm (context) - Baker - 1987
79 Learning sequential decision rules using simulation models a.. - Grefenstette, Ramsey et al. - 1990
50 Hierarchical genetic algorithms operating on populations of .. (context) - Koza - 1989
49 Credit assignment in rule discovery system based on genetic .. (context) - Grefenstette - 1988
49 Lamarckian learning in multi-agent environments - Grefenstette
36 An analysis of multi-point crossover - Spears, De Jong
33 Scheduling problems and traveling salesmen: The genetic edge.. (context) - Whitley, Starkweather et al. - 1989
26 Improving tactical plans with genetic algorithms - Schultz, Grefenstette - 1990
21 A formal analysis of the role of multi-point crossover in ge.. - De Jong, Spears - 1992
16 San Diego (context) - the, Conference et al. - 1991
15 Using neural networks and genetic algorithms as heuristics f.. - Spears, De Jong
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