This paper presents an approach to the Mario AI Benchmark problem, using the A* algorithm for navigation, and an evolutionary process combining routines for the reactiveness of the resulting bot. The Grammatical Evolution ...
We present an analysis of how the genotype-phenotype map in Grammatical Evolution (GE) can effect performance on the Max Problem. Earlier studies have demonstrated a performance decrease for Position independent Grammatical ...
Modularity has proven to be an important aspect of evolutionary computation. This work is concerned with discovering and using modules in one form of grammar-based genetic programming, grammatical evolution (GE). Previous ...
In this paper we present a new variant of the ant problem in the dynamic problem domain. This approach presents a functional dynamism to the problem landscape, where by the behaviour of the ant is driven by its ability to ...
We present a study of dynamic environments with genetic programming to ascertain if a dynamic environment can speed up evolution when compared to an equivalent static environment. We present an analysis of the types of ...
This paper investigates the applicability of Genetic Programming type systems to dynamic game environments. Grammatical Evolution was used to evolve Behaviour Trees, in order to create controllers for the Mario AI Benchmark. ...
This paper describes an Interactive Evolutionary system for generating pleasing 3D images using a combination of Grammatical Evolution and Jenn3d, a freely available visualiser of Cayley graphs of finite Coxeter groups. ...
There have been many approaches to modularity in the field of evolutionary computation, each tailored to function with a particular representation. This research examines one approach to modularity and grammar modification ...