Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

Download BibTeX

Title

Winning ant wars: evolving a human-competitive game strategy using fitnessless selection

Authors

[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2008

Chapter type

paper

Publication language

english

Abstract

EN We tell the story of BrilliAnt, the winner of the Ant Wars contest organized within GECCO’2007, Genetic and Evolutionary Computation Conference. The task for the Ant Wars contestants was to evolve a controller for a virtual ant that collects food in a square toroidal grid environment in the presence of a competing ant. BrilliAnt, submitted to the contest by our team, has been evolved through competitive one-population coevolution using genetic programming and a novel fitnessless selection method. In the paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its human-competitiveness, and describe selected behavioral patterns observed in its strategy.

Pages (from - to)

13 - 24

DOI

10.1007/978-3-540-78671-9_2

URL

https://link.springer.com/chapter/10.1007/978-3-540-78671-9_2

Book

Genetic programming: 11th European Conference, EuroGP 2008 Naples, Italy, March 26-28, 2008, Proceedings

Presented on

11th European Conference on Genetic Programming, EuroGP 2008, 26-28.03.2008, Naples, Italy

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.