Abstract
INTRODUCTION
We present an approach for automated evaluation and generation of videogames made with PuzzleScript, a description-based scripting language for authoring games, which was created by game designer Stephen Lavelle. We have developed a system that automatically discovers solutions for a multitude of videogames that each possess different game mechanics, rules, level designs, and win conditions. This was achieved by developing a set of general ruleset heuristics to assess the playability of a game based on its game mechanics. From the results of our approach, we showcase that a description-based language enables the development of general methods for automatically evaluating games authored with it. Additionally, we illustrate how an evolutionary approach can be used together with these methods to to automatically design alternate or novel game mechanics for authored games.
RELATED PUBLICATIONS
Chong-U Lim and D. Fox Harrell. (2014) “An Approach to General Videogame Evaluation and Automatic Generation using a Description Language”, Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG), Dortmund, Germany, 2014. 8 pp.
GITHUB REPOSITORY
This repository provides Artificial Intelligence extensions to Stephen Lavelle’s Puzzlescript, an open-source HTML5 Puzzle Game Engine available at http://www.puzzlescript.net
The PuzzleScript-AI extensions including the simulator and evolver were presented at the Computational Intelligence and Games 2014 Conference in Dortmund, Germany.
https://github.com/icelabMIT/PuzzleScriptAI
