Assessing the Effects of Interacting with MAP-Elites
Keywords:Quality-Diversity, Interactive Constrained MAP-Elites, Interactive Scenarios
AbstractMAP-Elites has been successfully applied to the generation of game content and robot behaviors. However, its behavior and performance when interacted with in co-creative systems is underexplored. This paper analyzes the implications of synthetic interaction for the stability and adaptability of MAP-Elites in such scenarios. We use pre-recorded human-made level design sessions with the Interactive Constrained MAP-Elites (IC MAP-Elites). To analyze the effect of each edition step in the search space over time using different feature dimensions, we introduce Temporal Expressive Range Analysis (TERA). With TERAs, MAP-Elites is assessed in terms of its adaptability and stability to generate diverse and high-performing individuals. Our results show that interactivity, in the form of design edits and MAP-Elites adapting towards them, directs the search process to previously unexplored areas of the fitness landscape and points towards how this could improve and enrich the co-creative process with quality-diverse individuals.
How to Cite
Alvarez, A., Font, J., Dahlskog, S., & Togelius, J. (2021). Assessing the Effects of Interacting with MAP-Elites. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 17(1), 124-131. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/18899