Terrain generation using genetic algorithms

  • Authors:
  • Teong Joo Ong;Ryan Saunders;John Keyser;John J. Leggett

  • Affiliations:
  • Texas A&M University, College Station, TX;Texas A&M University, College Station, TX;Texas A&M University, College Station, TX;Texas A&M University, College Station, TX

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a method for applying genetic algorithms to create 3D terrain data sets. Existing procedural algorithms for generation of terrain have several shortcomings. The most popular approach, fractal-based terrain generation, is efficient, but is difficult for a user to control. Other methods tend to require too much user input. In this paper, we provide an alternative method of terrain generation that uses a two-pass genetic algorithm approach to produce a variety of terrain types using only intuitive user inputs. We allow a user to specify a rough sketch of terrain region boundaries, and we refine these boundaries using a genetic algorithm. We then couple this with a database of given terrain data to generate an artificial terrain, which we optimize using a second genetic algorithm.