3 citations · 3 across the 1 of their papers we have counts for
Showing cs.AIShow all
3 papers · 1 filter
cs.AI2020
Learning the Designer's Preferences to Drive Evolution
Alberto Alvarez, Jose Font
This paper presents the Designer Preference Model, a data-driven solution that pursues to learn from user generated data in a Quality-Diversity Mixed-Initiative Co-Creativity (QD M…
cs.AI2020
Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature Dimensions
Alberto Alvarez, Steve Dahlskog, Jose Font +1
We propose the Interactive Constrained MAP-Elites, a quality-diversity solution for game content generation, implemented as a new feature of the Evolutionary Dungeon Designer: a mi…
cs.AI2019
Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
Alberto Alvarez, Steve Dahlskog, Jose Font +1
We propose the use of quality-diversity algorithms for mixed-initiative game content generation. This idea is implemented as a new feature of the Evolutionary Dungeon Designer, a s…