# A Controllable Co-Creative Agent for Game System Design

arXiv: https://arxiv.org/abs/2308.02317 · HTML: https://mlsanity.com/paper/2308.02317/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 4 Aug 2023.

## Builds on (most cited first, 3 of 3)

- [Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems](https://mlsanity.com/paper/2204.07666/) (2022)
- [Creative Wand: A System to Study Effects of Communications in Co-Creative Settings](https://mlsanity.com/paper/2208.02886/) (2022)
- [Lode Encoder: AI-constrained co-creativity](https://mlsanity.com/paper/2308.01312/) (2023)

## Built on by (most cited first, 2 of 2)

- [Game Generation via Large Language Models](https://mlsanity.com/paper/2404.08706/) (2024)
- [Unbounded: A Generative Infinite Game of Character Life Simulation](https://mlsanity.com/paper/2410.18975/) (2024)

## Abstract (arXiv)

Many advancements have been made in procedural content generation for games, and with mixed-initiative co-creativity, have the potential for great benefits to human designers. However, co-creative systems for game generation are typically limited to specific genres, rules, or games, limiting the creativity of the designer. We seek to model games abstractly enough to apply to any genre, focusing on designing game systems and mechanics, and create a controllable, co-creative agent that can collaborate on these designs. We present a model of games using state-machine-like components and resource flows, a set of controllable metrics, a design evaluator simulating playthroughs with these metrics, and an evolutionary design balancer and generator. We find this system to be both able to express a wide range of games and able to be human-controllable for future co-creative applications.