Preferential language biases which are introduced when using Tree-Adjoining Grammars in Grammatical Evolution affect the distribution of generated derivation structures, and as such, present difficulties when designing initialisation methods. Similar initial populations allow for a fairer comparison between different GP methods. This work proposes methods for dealing with these biases and exami...

In this paper, an Interactive Evolutionary system is described, which generates visually appealing 3D projections of mathematical constructs. This system uses a combination of the Grammatical Evolution paradigm and Jenn3d, a visualiser of Cayley graphs of finite Coxeter groups. A very compact representation is used for the genotype strings, using only 64 bits. The resulting visualisations, albe...

Adapting game content to a particular player’s needs and expertise constitutes an important aspect in game design. Most research in this direction has focused on adapting game difficulty to keep the player engaged in the game. Dynamic difficulty adjustment, however, focuses on one aspect of the gameplay experience by adjusting the content to increase or decrease perceived challenge. In this pap...

Intrusion detection on mobile Ad Hoc Networks (MANETs) is in its early stages. In this paper, we show how grammatical evolution can be used to evolve detection programs for dropping attacks, a particularly important attack type for such networks.

We describe a Genetic Algorithm that can evolve complete programs. Using a variable length linear genome to govern how a Backus Naur Form grammar deenition is mapped to a program, expressions and programs of arbitrary complexity may be evolved. Other automatic programming methods are described, before our system, Grammatical Evolution, is applied to a symbolic regression problem.

This paper introduces a novel approach for pairwise preference learning through a combination of an evolutionary method and random forest. Grammatical evolution is used to describe the structure of the trees in the Random Forest (RF) and to handle the process of evolution. Evolved random forests are evaluated based on their efficiency in predicting reported preferences. The combination of these...

Trade execution is concerned with the actual mechanics of buying or selling the desired amount of a financial instrument. Investors wishing to execute large orders face a tradeoff between market impact and opportunity cost. Trade execution strategies are designed to balance out these costs, thereby minimising total trading cost. Despite the importance of optimising the trade execution process, ...

It is well known that using high-locality representations is important for efficient evolutionary search. This paper investigates the locality of the genotype-phenotype mapping (representation) used in grammatical evolution (GE). The results show that the representation used in GE has problems with locality as many neighboring genotypes do not correspond to neighboring phenotypes. Experiments w...

Grammatical Evolution (GE) is a novel data-driven, model-induction tool, inspired by the biological gene-to-protein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to construct a series of models for the prediction of bankruptcy, employing information drawn from financial statements. Unlike prior studies in this domain, the raw financi...

Grammatical evolution (GE) is a form of grammar-based genetic programming. A particular feature of GE is that it adopts a distinction between the genotype and phenotype similar to that which exists in nature by using a grammar to map between the genotype and phenotype. This study seeks to extend our understanding of GE by examining the impact of different genotypic representations in order to d...