Exploring Representation in Evolutionary Level Design (Synthesis Lectures on Games and Computational Intelligence)

Automatic content generation is the production of content for games, web pages, or other purposes by procedural means. Search-based automatic content generation employs search-based algorithms to accomplish automatic content generation. This book presents a number of different techniques for search-based automatic content generation where the search algorithm is an evolutionary algorithm. The chapters treat puzzle design, the creation of small maps or mazes, the use of L-systems and a generalization of L-system to create terrain maps, the use of cellular automata to create maps, and, finally, the decomposition of the design problem for large, complex maps culminating in the creation of a map for a fantasy game module with designersupplied content and tactical features.

The evolutionary algorithms used for the different types of content are generic and similar, with the exception of the novel sparse initialization technique are presented in Chapter 2. The points where the content generation systems vary are in the design of their fitness functions and in the way the space of objects being searched is represented. A large variety of different fitness functions are designed and explained, and similarly radically different representations are applied to the design of digital objects all of which are, essentially, maps for use in games.

Dr. Daniel Ashlock is a professor of mathematics at the University of Guelph in Guelph, Ontario, Canada. He is a member of the IEEE Computational Intelligence Society Games Technical Committee, serves as an associate editor of both the IEEE Transactions on Games and the new journal Game and Puzzle Design. Dr. Ashlock is a lifelong referee of roleplaying games and loves the problems that arise in game and puzzle design. He is the author of 270 peer-reviewed scientific publications, about one-third of which are on the topic of games. Across his work the issue of representation, the study of how to phrase problems for the computer, appears in a starring role. Dr. Ashlock is the Chief of Innovation at Ashlock and McGuinness Consulting, Inc.