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EUROGP
2010
Springer
160views Optimization» more  EUROGP 2010»
14 years 11 months ago
Improving the Generalisation Ability of Genetic Programming with Semantic Similarity based Crossover
This paper examines the impact of semantic control on the ability of Genetic Programming (GP) to generalise via a semantic based crossover operator (Semantic Similarity based Cross...
Nguyen Quang Uy, Nguyen Thi Hien, Nguyen Xuan Hoai...
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
14 years 11 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
GECCO
2008
Springer
117views Optimization» more  GECCO 2008»
14 years 11 months ago
Is "best-so-far" a good algorithmic performance metric?
In evolutionary computation, experimental results are commonly analyzed using an algorithmic performance metric called best-so-far. While best-so-far can be a useful metric, its u...
Nathaniel P. Troutman, Brent E. Eskridge, Dean F. ...
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
14 years 11 months ago
Potential fitness for genetic programming
We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation ...
Krzysztof Krawiec, PrzemysBaw Polewski
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
14 years 11 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen