# Mechanic Maker: Accessible Game Development Via Symbolic Learning Program Synthesis

arXiv: https://arxiv.org/abs/2410.01096 · HTML: https://mlsanity.com/paper/2410.01096/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 43 references that are in the map.
- First posted on arXiv 1 Oct 2024.

## Builds on (most cited first, 8 of 8)

- [World Models](https://mlsanity.com/paper/1803.10122/) (2018)
- [Conceptual Game Expansion](https://mlsanity.com/paper/2002.09636/) (2020)
- [Lode Encoder: AI-constrained co-creativity](https://mlsanity.com/paper/2308.01312/) (2023)
- [Evaluation of a Recommender System for Assisting Novice Game Designers](https://mlsanity.com/paper/1908.04629/) (2019)
- [Mechanic Maker 2.0: Reinforcement Learning for Evaluating Generated Rules](https://mlsanity.com/paper/2309.09476/) (2023)
- [Design-Driven Requirements for Computationally Co-Creative Game AI Design Tools](https://mlsanity.com/paper/2107.13738/) (2021)
- [Toward Co-creative Dungeon Generation via Transfer Learning](https://mlsanity.com/paper/2107.12533/) (2021)
- [Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systems](https://mlsanity.com/paper/2205.09269/) (2022)

## Built on by (most cited first, 3 of 3)

- [Cardiverse: Harnessing LLMs for Novel Card Game Prototyping](https://mlsanity.com/paper/2502.07128/) (2025)
- [Mortar: Evolving Mechanics for Automatic Game Design](https://mlsanity.com/paper/2601.00105/) (2025)
- [An Exploration of Collision-based Enemy Morphology Generation](https://mlsanity.com/paper/2606.02832/) (2026)

## Abstract (arXiv)

Game development is a highly technical practice that traditionally requires programming skills. This serves as a barrier to entry for would-be developers or those hoping to use games as part of their creative expression. While there have been prior game development tools focused on accessibility, they generally still require programming, or have major limitations in terms of the kinds of games they can make. In this paper we introduce Mechanic Maker, a tool for creating a wide-range of game mechanics without programming. It instead relies on a backend symbolic learning system to synthesize game mechanics from examples. We conducted a user study to evaluate the benefits of the tool for participants with a variety of programming and game development experience. Our results demonstrated that participants' ability to use the tool was unrelated to programming ability. We conclude that tools like ours could help democratize game development, making the practice accessible regardless of programming skills.