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GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 7 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay
JCB
2000
137views more  JCB 2000»
13 years 7 months ago
NOTUNG: A Program for Dating Gene Duplications and Optimizing Gene Family Trees
Large scale gene duplication is a major force driving the evolution of genetic functional innovation. Whole genome duplications are widely believed to have played an important rol...
Kevin Chen, Dannie Durand, Martin Farach-Colton
ICSE
1999
IEEE-ACM
13 years 11 months ago
Dynamically Discovering Likely Program Invariants to Support Program Evolution
ÐExplicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code. In practice, however, these invariants are...
Michael D. Ernst, Jake Cockrell, William G. Griswo...
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
13 years 11 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2006
Springer
213views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolutionary unit testing of object-oriented software using strongly-typed genetic programming
Evolutionary algorithms have successfully been applied to software testing. Not only approaches that search for numeric test data for procedural test objects have been investigate...
Stefan Wappler, Joachim Wegener