An approach to general videogame evaluation and automatic generation using a description language

In this paper, 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 [1]. 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. In our approach, we first developed a set of general level state heuristics, which estimates how close a given game level is to being solved. It is used to adapt the best-first search algorithm to implement a general evaluation approach for PuzzleScript games called GEBestFS. Next, we developed an evolutionary framework that automatically generates novel game mechanics from scratch by evolving game design rulesets and evaluating them using GEBestFS. 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.

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