gramEvol: Grammatical Evolution in R

Grammatical Evolution: A Tutorial using gramEvol

Grammatical Evolution by Grammatical Evolution: The Evolution of Grammar and Genetic Code

This study examines the possibility of evolving the grammar that Grammatical Evolution uses to specify the construction of a syntactically correct solution. As the grammar dictates the space of symbols that can be used in a solution, its evolution represents the evolution of the genetic code itself. Results provide evidence to show that the coevolution of grammar and genetic code with a solutio...

Grammatical Evolution: STE criterion in Symbolic Regression Task

Grammatical evolution (GE) is one of the newest among computational methods (Ryan et al., 1998), (O’Neill and Ryan, 2001). Basically, it is a tool used to automatically generate Backus-Naur-Form (BNF) computer programmes. The method's evolution mechanism may be based on a standard genetic algorithm (GA). GE is very often used to solve the problem of a symbolic regression, determining a module's...

GDF: A tool for function estimation through grammatical evolution

This article introduces a tool for data fitting that is based on genetic programming and especially on the grammatical evolution technique. The user needs to input a series of points and the accompanied dimensionality n and the tool will produce via the genetic programming paradigm a function f :Rn → R which is an approximate solution to the symbolic regression problem. The tool is entirely wri...

Evolution Hyper - heuristic for Combinatorial Optimization problems

Designing generic problem solvers that perform well across a diverse set of problems is a challenging task. In this work, we propose a hyper-heuristic framework to automatically generate an effective and generic solution method by utilizing grammatical evolution. In the proposed framework, grammatical evolution is used as an online solver builder, which takes several heuristic components (e.g. ...