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GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
13 years 11 months ago
An analysis of constructive crossover and selection pressure in genetic programming
A common problem in genetic programming search algorithms is destructive crossover in which the offspring of good parents generally has worse performance than the parents. Design...
Huayang Xie, Mengjie Zhang, Peter Andreae
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
13 years 11 months ago
Improving the human readability of features constructed by genetic programming
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming a...
Matthew Smith, Larry Bull
GECCO
2007
Springer
186views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving controllers for simulated car racing using object oriented genetic programming
Several different controller representations are compared on a non-trivial problem in simulated car racing, with respect to learning speed and final fitness. The controller rep...
Alexandros Agapitos, Julian Togelius, Simon M. Luc...
GECCO
2007
Springer
165views Optimization» more  GECCO 2007»
13 years 11 months ago
Peptide detectability following ESI mass spectrometry: prediction using genetic programming
The accurate quantification of proteins is important in several areas of cell biology, biotechnology and medicine. Both relative and absolute quantification of proteins is often d...
David C. Wedge, Simon J. Gaskell, Simon J. Hubbard...
GECCO
2007
Springer
207views Optimization» more  GECCO 2007»
13 years 11 months ago
A data parallel approach to genetic programming using programmable graphics hardware
In recent years the computing power of graphics cards has increased significantly. Indeed, the growth in the computing power of these graphics cards is now several orders of magn...
Darren M. Chitty
EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
13 years 11 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
EUROGP
2007
Springer
164views Optimization» more  EUROGP 2007»
13 years 11 months ago
The Induction of Finite Transducers Using Genetic Programming
This paper reports on the results of a preliminary study conducted to evaluate genetic programming (GP) as a means of evolving finite state transducers. A genetic programming syste...
Amashini Naidoo, Nelishia Pillay
FBIT
2007
IEEE
13 years 11 months ago
Developmental Evaluation in Genetic Programming: A Position Paper
—Standard genetic programming genotypes are generally highly disorganized and poorly structured, with little code replication. This is also true of existing developmental genetic...
Tuan Hao Hoang, Robert I. McKay, Daryl Essam, Nguy...
CEC
2007
IEEE
13 years 11 months ago
Computational intelligence algorithms for risk-adjusted trading strategies
Abstract— This paper investigates the performance of trading strategies identified through Computational Intelligence techniques. We focus on trading rules derived by Genetic Pr...
Nicos G. Pavlidis, E. G. Pavlidis, Michael G. Epit...
IPPS
2008
IEEE
13 years 11 months ago
A genetic programming approach to solve scheduling problems with parallel simulation
—Scheduling and dispatching are two ways of solving production planning problems. In this work, based on preceding works, it is explained how these two approaches can be combined...
Andreas Beham, Stephan M. Winkler, Stefan Wagner 0...