# GAVEL: Generating Games Via Evolution and Language Models

arXiv: https://arxiv.org/abs/2407.09388 · HTML: https://mlsanity.com/paper/2407.09388/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 68 references that are in the map.
- First posted on arXiv 12 Jul 2024.

## Builds on (most cited first, 28 of 28)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [A Survey of Large Language Models](https://mlsanity.com/paper/2303.18223/) (2023)
- [Code Llama: Open Foundation Models for Code](https://mlsanity.com/paper/2308.12950/) (2023)
- [Eureka: Human-Level Reward Design via Coding Large Language Models](https://mlsanity.com/paper/2310.12931/) (2023)
- [Illuminating search spaces by mapping elites](https://mlsanity.com/paper/1504.04909/) (2015)
- [PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models](https://mlsanity.com/paper/2109.05093/) (2021)
- [A Systematic Evaluation of Large Language Models of Code](https://mlsanity.com/paper/2202.13169/) (2022)
- [Efficient Training of Language Models to Fill in the Middle](https://mlsanity.com/paper/2207.14255/) (2022)
- [Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts](https://mlsanity.com/paper/2402.16822/) (2024)
- [Evolution through Large Models](https://mlsanity.com/paper/2206.08896/) (2022)
- [Quality and Diversity Optimization: A Unifying Modular Framework](https://mlsanity.com/paper/1708.09251/) (2017)
- [Motif: Intrinsic Motivation from Artificial Intelligence Feedback](https://mlsanity.com/paper/2310.00166/) (2023)
- [Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs](https://mlsanity.com/paper/2306.03081/) (2023)
- [Level Generation Through Large Language Models](https://mlsanity.com/paper/2302.05817/) (2023)
- [Using Centroidal Voronoi Tessellations to Scale Up the Multi-dimensional Archive of Phenotypic Elites Algorithm](https://mlsanity.com/paper/1610.05729/) (2016)
- [Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors](https://mlsanity.com/paper/1905.11874/) (2019)
- [EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents](https://mlsanity.com/paper/2403.12014/) (2024)
- [Procedural Content Generation through Quality Diversity](https://mlsanity.com/paper/1907.04053/) (2019)
- [Ludii -- The Ludemic General Game System](https://mlsanity.com/paper/1905.05013/) (2019)
- [pyribs: A Bare-Bones Python Library for Quality Diversity Optimization](https://mlsanity.com/paper/2303.00191/) (2023)
- [General Video Game Rule Generation](https://mlsanity.com/paper/1906.05160/) (2019)
- [Automated Game Design via Conceptual Expansion](https://mlsanity.com/paper/1809.02232/) (2018)
- [The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game Designer](https://mlsanity.com/paper/2403.02454/) (2024)
- [General Board Game Concepts](https://mlsanity.com/paper/2107.01078/) (2021)
- [Automatic Game Design via Mechanic Generation](https://mlsanity.com/paper/1908.01420/) (2019)
- [Measuring Board Game Distance](https://mlsanity.com/paper/2301.03913/) (2023)
- [Automated Game Design Learning](https://mlsanity.com/paper/1707.03333/) (2017)

## Built on by (most cited first, 24 of 24)

- [Assessing Adaptive World Models in Machines with Novel Games](https://mlsanity.com/paper/2507.12821/) (2025)
- [Boundless Socratic Learning with Language Games](https://mlsanity.com/paper/2411.16905/) (2024)
- [AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games](https://mlsanity.com/paper/2602.17594/) (2026)
- [Grammar-based Game Description Generation using Large Language Models](https://mlsanity.com/paper/2407.17404/) (2024)
- [EvoCAD: Evolutionary CAD Code Generation with Vision Language Models](https://mlsanity.com/paper/2510.11631/) (2025)
- [From Code to Play: Benchmarking Program Search for Games Using Large Language Models](https://mlsanity.com/paper/2412.04057/) (2024)
- [PuzzleJAX: A Benchmark for Reasoning and Learning](https://mlsanity.com/paper/2508.16821/) (2025)
- [Grammar and Gameplay-aligned RL for Game Description Generation with LLMs](https://mlsanity.com/paper/2503.15783/) (2025)
- [ScriptDoctor: Automatic Generation of PuzzleScript Games via Large Language Models and Tree Search](https://mlsanity.com/paper/2506.06524/) (2025)
- [Boardwalk: Towards a Framework for Creating Board Games with LLMs](https://mlsanity.com/paper/2508.16447/) (2025)
- [Narrative-to-Scene Generation: An LLM-Driven Pipeline for 2D Game Environments](https://mlsanity.com/paper/2509.04481/) (2025)
- [From Gameplay Traces to Game Mechanics: Causal Induction with Large Language Models](https://mlsanity.com/paper/2602.00190/) (2026)
- [REFLEX: Reflective Evolution from LLM Experience](https://mlsanity.com/paper/2606.16496/) (2026)
- [Open Role-Playing with Delta-Engines](https://mlsanity.com/paper/2408.05842/) (2024)
- [Exploring RL-based LLM Training for Formal Language Tasks with Programmed Rewards](https://mlsanity.com/paper/2410.17126/) (2024)
- [Anytime Sequential Halving in Monte-Carlo Tree Search](https://mlsanity.com/paper/2411.07171/) (2024)
- [Vector Quantized-Elites: Unsupervised and Problem-Agnostic Quality-Diversity Optimization](https://mlsanity.com/paper/2504.08057/) (2025)
- [Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs](https://mlsanity.com/paper/2509.08847/) (2025)
- [Mortar: Evolving Mechanics for Automatic Game Design](https://mlsanity.com/paper/2601.00105/) (2025)
- [A Research Agenda for Usability and Generalisation in Reinforcement Learning](https://mlsanity.com/paper/2412.16970/) (2024)
- [Ludax: A GPU-Accelerated Domain Specific Language for Board Games](https://mlsanity.com/paper/2506.22609/) (2025)
- [Usando LLMs para Programar Jogos de Tabuleiro e Variacc~oes](https://mlsanity.com/paper/2511.05114/) (2025)
- [Programmable Cellular Automata](https://mlsanity.com/paper/2609.06102/) (2026)
- [World Agent: Can Language Models Keep a World Running?](https://mlsanity.com/paper/2609.32692/) (2026)

## Abstract (arXiv)

Automatically generating novel and interesting games is a complex task. Challenges include representing game rules in a computationally workable form, searching through the large space of potential games under most such representations, and accurately evaluating the originality and quality of previously unseen games. Prior work in automated game generation has largely focused on relatively restricted rule representations and relied on domain-specific heuristics. In this work, we explore the generation of novel games in the comparatively expansive Ludii game description language, which encodes the rules of over 1000 board games in a variety of styles and modes of play. We draw inspiration from recent advances in large language models and evolutionary computation in order to train a model that intelligently mutates and recombines games and mechanics expressed as code. We demonstrate both quantitatively and qualitatively that our approach is capable of generating new and interesting games, including in regions of the potential rules space not covered by existing games in the Ludii dataset. A sample of the generated games are available to play online through the Ludii portal.