Searching for Balanced 2D Brawler Games: Successes and Failures of Automated Evaluation

Abstract

Automated game design (AGD) research focuses on creating systems that can design entirely new games. This is often done by a genetic algorithm, with a fitness function that is used to find individual games that satisfy certain design criteria. However, it is difficult to tell if generated games actually have the desired emergent properties (such as balance), since the fitness function might not align well with human aesthetic judgments about such properties. This is particularly problematic when trying to automatically design balanced, fair, yet asymmetrical games for multiple players. In this paper we present an implementation of an optimization-based AGD system for brawler games, and present findings from a preliminary user study of generated games. We show that while the system successfully optimizes for our written fitness function during human play, we found that this optimization did not necessarily translate to our hypothesized human experience of the game.