Grammar formalisms are one of the key representation structures in Computer Science. So it
is not surprising that they have also become important as a method for formalizing …

Grammatical Evolution (GE) is a population-based evolutionary algorithm, where a formal
grammar is used in the genotype to phenotype map** process. PonyGE2 is an open …

The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …

This paper presents the use of design grammars to evolve playable 2D platform levels
through grammatical evolution (GE). Representing levels using design grammars allows …

The fields of machine meta-learning and hyper-heuristic optimisation have developed
mostly independently of each other, although evolutionary algorithms (particularly genetic …

In this paper we propose GESwarm, a novel tool that can automatically synthesize collective
behaviors for swarms of autonomous robots through evolutionary robotics. Evolutionary …

We describe an R package which implements grammatical evolution (GE) for automatic
program generation. By performing an unconstrained optimization over a population of R …

Abstract This paper introduces Structured Grammatical Evolution, a new genotypic
representation for Grammatical Evolution, where each gene is explicitly linked to a non …

Genetic Programming (GP) is an heuristic method that can be applied to many Machine
Learning, Optimization and Engineering problems. In particular, it has been widely used in …

This article presents a novel method, called Modular Grammatical Evolution (MGE), toward
validating the hypothesis that restricting the solution space of NeuroEvolution to modular …