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PPSN
2004
Springer
15 years 8 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
96
Voted
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 8 months ago
Multi-chromosomal genetic programming
This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by...
Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell
SBBD
2004
82views Database» more  SBBD 2004»
15 years 4 months ago
Optimizing Ranking Calculation in Web Search Engines: a Case Study
Web search engines compete to offer the fastest responses with highest relevance. However, as Web collections grow, it becomes more difficult to achieve this purpose. As most user...
Miguel Costa, Mário J. Silva
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
15 years 6 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
122
Voted
PPSN
2004
Springer
15 years 8 months ago
SPEA2+: Improving the Performance of the Strength Pareto Evolutionary Algorithm 2
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...