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» Evolutionary algorithms and matroid optimization problems
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GECCO
2011
Springer
232views Optimization» more  GECCO 2011»
12 years 11 months ago
Mutation rates of the (1+1)-EA on pseudo-boolean functions of bounded epistasis
When the epistasis of the fitness function is bounded by a constant, we show that the expected fitness of an offspring of the (1+1)-EA can be efficiently computed for any point...
Andrew M. Sutton, Darrell Whitley, Adele E. Howe
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
14 years 8 hour ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
14 years 2 months ago
GAMA (genetic algorithm driven multi-agents)for e-commerce integrative negotiation
Software agents help automate a variety of tasks including those involved in buying and selling products over the internet. The need for handling complex highly configurable produ...
Magda Bahaa Eldin Fayek, Ihab A. Talkhan, Khalil S...
PPSN
2004
Springer
14 years 1 months ago
Indicator-Based Selection in Multiobjective Search
Abstract. This paper discusses how preference information of the decision maker can in general be integrated into multiobjective search. The main idea is to first define the opti...
Eckart Zitzler, Simon Künzli
FSTTCS
2003
Springer
14 years 29 days ago
Comparing Sequences with Segment Rearrangements
Computational genomics involves comparing sequences based on “similarity” for detecting evolutionary and functional relationships. Until very recently, available portions of th...
Funda Ergün, S. Muthukrishnan, Süleyman ...