Now showing 1 - 7 of 7
  • Publication
    Evolutionary design using grammatical evolution and shape grammars : designing a shelter
    A new evolutionary design tool is presented, which uses shape grammars and a grammar-based form of evolutionary computation, grammatical evolution (GE). Shape grammars allow the user to specify possible forms, and GE allows forms to be iteratively selected, recombined and mutated: this is shown to be a powerful combination of techniques. The potential of GE and shape grammars for evolutionary design is examined by attempting to design a single-person shelter to be evaluated by collaborators from the University College Dublin School of Architecture, Landscape, and Engineering. The team was able to successfully generate conceptual shelter designs based on scrutiny from the collaborators. A number of avenues for future work are highlighted arising from the case study.
      1751
  • Publication
    Evolving a Ms. PacMan controller using grammatical evolution
    In this paper we propose an evolutionary approach capable of successfully combining rules to play the popular video game, Ms. Pac- Man. In particular we focus our attention on the benefits of using Gram- matical Evolution to combine rules in the form of “if then perform ”. We defined a set of high-level functions that we think are necessary to successufully maneuver Ms. Pac-Man through a maze while trying to get the highest possible score. For comparison purposes, we used four Ms. Pac-Man agents, including a hand-coded agent, and tested them against three different ghosts teams. Our approach shows that the evolved controller achieved the highest score among all the other tested controllers, regardless of the ghost team used.
      748Scopus© Citations 19
  • Publication
    A non-destructive grammar modification approach to modularity in grammatical evolution
    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 work has shown that simply adding modules to GE’s grammar has the potential to disrupt fit individuals developed by evolution up to that point. This paper presents a solution to prevent the disturbance in fitness that can come with modifying GE’s grammar with previously discovered modules. The results show an increase in performance from a previously examined grammar modification approach and also an increase in performance when compared to standard GE.
      419Scopus© Citations 13
  • Publication
    Comparing the performance of the evolvable πgrammatical evolution genotype-phenotype pap to grammatical evolution in the dynamic Ms. Pac-Man environment
    In this work, we examine the capabilities of two forms of mappings by means of Grammatical Evolution (GE) to successfully generate controllers by combining high-level functions in a dynamic environment. In this work we adopted the Ms. Pac-Man game as a benchmark test bed. We show that the standard GE mapping and Position Independent GE (πGE) mapping achieve similar performance in terms of maximising the score. We also show that the controllers produced by both approaches have an overall better performance in terms of maximising the score compared to a hand-coded agent. There are, however, significant differences in the controllers produced by these two approaches: standard GE produces more controllers with invalid code, whereas the opposite is seen with πGE.
      502Scopus© Citations 11
  • Publication
    Exploring grammatical modification with modules in grammatical evolution
    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 with a grammar-based approach to genetic programming, grammatical evolution (GE). Here, GE’s grammar was modified over the course of an evolutionary run with modules in order to facilitate their appearance in the population. This is the first step in what will be a series of analysis on methods of modifying GE’s grammar to enhance evolutionary performance. The results show that identifying modules and using them to modify GE’s grammar can have a negative effect on search performance when done improperly. But, if undertaken thoughtfully, there are possible benefits to dynamically enhancing the grammar with modules identified during evolution.
      341Scopus© Citations 10
  • Publication
    An examination on the modularity of grammars in grammatical evolutionary design
    This work furthers the understanding of modularity in grammar-based genetic programming approaches by analyzing how different grammars may be capable of producing the same phenotypes, but still display differences in performance on the same problems. This is done by creating four grammars with varying levels of modularity and using them with grammatical evolution to evolve floor plan designs. The results of this experimentation show how increases in modularity, brought about by simple modifications in the grammars, and increases in the quality of solutions go hand in hand. It also demonstrates how more modular grammars explore more individuals even while fitness remains the same or changes in only minor increments.
      398Scopus© Citations 2
  • Publication
    Higher-order functions in aesthetic EC encodings
    The use of higher-order functions, as a method of abstraction and re-use in EC encodings, has been the subject of relatively little research. In this paper we introduce and give motivation for the ideas of higher-order functions, and describe their general advantages in EC encodings. We implement grammars using higher-order ideas for two problem domains, music and 3D architectural design, and use these grammars in the grammatical evolution paradigm. We demonstrate four advantages of higher-order functions (patterning of phenotypes, non-entropic mutations, compression of genotypes, and natural expression of artistic knowledge) which lead to beneficial results on our problems.
      675Scopus© Citations 12