Multi Expression Programming (MEP) is an evolutionary algorithm for generating mathematical functions describing a given set of data. MEP is a Genetic...

expression programming (GEP) in computer programming is an evolutionary algorithm that creates computer programs or models. These computer programs are...

representation Grammatical evolution Inductive programming Linear genetic programming Multi expression programming Propagation of schema "BEAGLE A Darwinian...

element of such an array. Multi expression programming Cartesian genetic programming Grammatical evolution Genetic programming M. Brameier, W. Banzhaf,...

of the different classes. Multi expression programming (MEP) is an evolutionary algorithm for generating computer programs (that can be used for classification...

and more. Genetic programming Gene expression programming Grammatical evolution Linear genetic programming Multi expression programming Miller, J.F., Thomson...

Programming: Cartesian genetic programming Gene expression programming Grammatical evolution Linear genetic programming Multi expression programming Evolutionary...

Mohammad A.; Elazouni, Ashraf (30 November 2021). "Modified multi-objective evolutionary programming algorithm for solving project scheduling problems". Expert...

Genetic Programming, including Cartesian genetic programming, Gene expression programming, grammatical evolution, Linear genetic programming, Multi expression...

In computer programming, an S-expression (or symbolic expression, abbreviated as sexpr or sexp) is an expression in a like-named notation for nested list...

Programming languages can be grouped by the number and types of paradigms supported. A concise reference for the programming paradigms listed in this article...

are fuzzy systems constructed by using genetic algorithms or genetic programming, which mimic the process of natural evolution, to identify its structure...

Multi-stage programming (MSP) is a variety of metaprogramming in which compilation is divided into a series of intermediate phases, allowing typesafe...

evolution strategies, genetic programming and evolutionary programming. In his book discussing the use of genetic programming for the optimization of complex...

implementation of Gene expression programming technique for various problems including symbolic regression (commercial) Multi Expression Programming X, an implementation...

The expression problem is a challenging problem in programming languages that concerns the extensibility and modularity of statically typed data abstractions...

and the books also contain surveys of application areas. Surveys on the multi-faceted research aspects of DE can be found in journal articles. A basic...

high-level, strongly typed, multi-paradigm programming language that encompasses functional, imperative, and object-oriented programming methods. It is most often...

pp. 2–9, ISBN 1-55860-208-9 Koza, John R. (1992). Genetic programming : on the programming of computers by means of natural selection. Cambridge, Mass...

Logistic regression Probit model Genetic Programming Multi expression programming Linear genetic programming Each classifier is best in only a select...

programming languages, with C compilers available for practically all modern computer architectures and operating systems. The book The C Programming...

interpolation Linear trend estimation Mathematical model Multi expression programming Multi-curve framework and Bootstrapping (finance) Nonlinear regression...

Evolutionary algorithm Genetic algorithm Evolutionary programming Genetic programming Gene expression programming Grammatical evolution Evolution strategy Learnable...

logic Gaussian process Genetic programming Gene expression programming Hidden Markov model Multi expression programming Queueing theory analysis Control...

important component of evolutionary algorithms (EA), such as genetic programming, evolution strategies or genetic algorithms. An EA is a metaheuristic...

model relying on a quadratic approximation. In 2025, Chen et.al. proposed a multi-agent evolution strategy for consensus-based distributed optimization, where...

based GA Genetic programming (GP) Cartesian GP Linear GP Gene expression programming Grammatical evolution Multi expression programming Differential evolution...

Genetic programming Java Grammatical Evolution Cartesian genetic programming Gene expression programming Linear genetic programming Multi expression programming...

based GA Genetic programming (GP) Cartesian GP Linear GP Gene expression programming Grammatical evolution Multi expression programming Differential evolution...

Parity problems are widely used as benchmark problems in genetic programming but inherited from the artificial neural network community. Parity is calculated...