Procedural weapons generation for unreal tournament III

Design a set of weapons for a competitive first person shooter (FPS) is not an easy task: it involves several challenges, such as balancing, diversity, and novelty. In this paper, we combine procedural content generation and evolutionary computation to solve this complex task. In particular, we introduce a novel approach to procedurally generate weapons for Unreal Tournament III, a popular commercial FPS. In our approach, each weapon is represented as a parameters vector and evaluated based on game statistics. We tested our approach on three different application scenarios that represents three typical design problems: (i) create a balanced set of weapons, (ii) improve a given weapon with the least possible changes, and (iii) create a set of weapons with some specific design goals. Finally, we also performed a preliminary user study to validate our work. Our results are promising and suggest that the proposed approach might be successfully used to support the weapon design process.