Evolving recurrent models using linear GP
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
On evolving buffer overflow attacks using genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Genetic parallel programming: design and implementation
Evolutionary Computation
FuzzyTree crossover for multi-valued stock valuation
Information Sciences: an International Journal
A survey and taxonomy of performance improvement of canonical genetic programming
Knowledge and Information Systems
Automatic system identification based on coevolution of models and tests
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A linear genetic programming approach to intrusion detection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Parallel programs are more evolvable than sequential programs
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
802.11 de-authentication attack detection using genetic programming
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Context-Based repeated sequences in linear genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Using code bloat to obfuscate evolved network traffic
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Network protocol discovery and analysis via live interaction
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Parallel linear genetic programming for multi-class classification
Genetic Programming and Evolvable Machines
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Page-based linear genetic programming (GP) is proposed in which individuals are described in terms of a number of pages. Pages are expressed in terms of a fixed number of instructions, which is constant for all individuals in the population. Pairwise crossover results in the swapping of single pages, and thus, individuals are of a fixed number of instructions. Head-to-head comparison with Tree-structured GP and block-based linear GP indicates that the page-based approach evolves succinct solutions without penalizing generalization ability