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Everything about Genetic programming
Evolving computer programs with techniques analogous to natural genetic processes
Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population of programs. It applies the genetic operators selection according to a predefined fitness measure, mutation and crossover. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Genetic programmingA 5-minute orientation
- Skim a recent paper: Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran ProgramInfluential work since 2022
- Pick up a classic book: The GeneThe most-reprinted book on the subject
- Read the landmark paper: Epigenetic programming by maternal behaviorCited 5,101 times
- Go sideways: Evolutionary computationA closely related topic
- Go sideways: Java Evolutionary Computation ToolkitA closely related topic
📖 Definitions
Noun A population-based evolutionary computation method for the automatic synthesis and optimization of computer programs.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Epigenetic programming by maternal behavior
Strongly Typed Genetic Programming
Open issues in genetic programming
Genetic-algorithm programming environments
Fault detection using genetic programming
Genetic programming
Genetic programming for shader simplification
Genetic programming for multitimescale modeling
🆕 Influential since 2022
Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Explainable Artificial Intelligence by Genetic Programming: A Survey
A Comparison of Several Linear Genetic Programming Techniques
Optogenetics for transcriptional programming and genetic engineering
Genetic programming for automatic skin cancer image classification
📚 Books worth reading
The GeneSiddhartha Mukherjee, Dennis Boutsikaris · 2016
Genetic and Evolutionary ComputingJeng-Shyang Pan, Jerry Chun-Wei Lin · 2013
The Practical Handbook of Genetic AlgorithmsLance D. Chambers · 1995
Essentials of GeneticsWilliam S. Klug, Michael R. Cummings · 2002
Artificial evolutionPierre Collet, Jin-Kao Hao · 2002
Genetic ProgrammingPenousal Machado, Malcolm I. Heywood · 2015
Genetic algorithms for pattern recognitionSankar K. Pal, Paul P. Wang · 1996
Applied genetic programming and machine learningHitoshi Iba · 2009
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Java Evolutionary Computation Toolkit ECJ is a freeware evolutionary computation research system written in Java. It is a framework that supports a variety of evolutionary computation techniques…
- Genetic algorithm A genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA)…
- Grammatical evolution Grammatical evolution (GE) is a genetic programming (GP) technique (or approach) from evolutionary computation pioneered by Conor Ryan, JJ Collins and…
- Genetic operator A genetic operator is an operator used in evolutionary algorithms (EA) to guide the algorithm towards a solution to a given problem. There are three main…
- Genetic representation In computer programming, genetic representation is a way of presenting solutions/individuals in evolutionary computation methods. The term encompasses…
- Chromosome (evolutionary algorithm) A chromosome or genotype in evolutionary algorithms (EA) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm…
- Mutation (evolutionary algorithm) Mutation is a genetic operator used to maintain genetic diversity of the chromosomes of a population of an evolutionary algorithm (EA), including genetic…