This contribution introduces analytical programming, a novel method that allows solving various problems from the symbolic regression domain. Symbolic regression was first proposed by J. R. Koza in his genetic programming and by C. Ryan in grammatical evolution. This contribution explains the main principles of analytic programming, and demonstrates its ability to synthesize suitable solutions,...

Recent advances in automatic algorithm configuration have made it possible to configure very flexible algorithmic frameworks in order to fine-tune them for particular problems. This is often done by the use of automatic methods to set the values of algorithm parameters. A rather different approach uses grammatical evolution, where the possible algorithms are implicitly defined by a context-free...

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...

A number of disparate approaches to language, ranging from cognitive linguistics to stochastic implementations of optimality theory, have challenged the classical distinction between knowledge of language and use of language. Supporters of such approaches point to the functional motivation of grammatical structure, language users’ sensitivity to the frequency of occurrence of grammatical elemen...

This review concentrates on two different language dimensions: lexical/semantic and grammatical. This distinction between a lexical/semantic system and a grammatical system is well known in linguistics, but in cognitive neurosciences it has been obscured by the assumption that there are several forms of language disturbances associated with focal brain damage and hence language includes a diver...

In a previous work, the authors proposed a Grammatical Evolution algorithm to automatically generate Lindenmayer Systems which represent fractal curves with a pre-determined fractal dimension. This paper gives strong statistical evidence that the probability distributions of the execution time of that algorithm exhibits a heavy tail with an hyperbolic probability decay for long executions, whic...

Motivation: Multiple models exist to describe the topology and the dynamical behavior of gene regulatory networks (GRNs). Among them, symbolic models (such as systems of ordinary differential equations) have the advantage of providing intuitive insights into the inner workings of a network so that general laws can be derived. Obtaining such models from time series data has proven to be a diffic...

Grammatical inference of context-free grammars using positive and negative language examples is among the most challenging task in modern artificial natural technology. Recently, several implementations combining various techniques, usually including Backus–Naur form, have been proposed. In this paper, we explore a new implementation grammatical evolution methods focused on Greibach normal form...

Semantic maps have offered linguists an appealing and empirically rooted methodology for describing recurrent structural patterns in language development and the multifunctionality of grammatical categories. Although some researchers argue that semantic maps are universal and given, others provide evidence that there are no fixed or universal maps. This paper takes the position that semantic ma...