# General Game Heuristic Prediction Based on Ludeme Descriptions

arXiv: https://arxiv.org/abs/2105.12846 · HTML: https://mlsanity.com/paper/2105.12846/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 17 references that are in the map.
- First posted on arXiv 26 May 2021.

## Builds on (most cited first, 2 of 2)

- [Ludii -- The Ludemic General Game System](https://mlsanity.com/paper/1905.05013/) (2019)
- [Modern Techniques for Ancient Games](https://mlsanity.com/paper/2101.10066/) (2020)

## Built on by (most cited first, 7 of 7)

- [General Board Game Concepts](https://mlsanity.com/paper/2107.01078/) (2021)
- [Grammar-based Game Description Generation using Large Language Models](https://mlsanity.com/paper/2407.17404/) (2024)
- [Measuring Board Game Distance](https://mlsanity.com/paper/2301.03913/) (2023)
- [Automatic Generation of Board Game Manuals](https://mlsanity.com/paper/2109.09507/) (2021)
- [Grammar and Gameplay-aligned RL for Game Description Generation with LLMs](https://mlsanity.com/paper/2503.15783/) (2025)
- [Towards Explaining Monte-Carlo Tree Search by Using Its Enhancements](https://mlsanity.com/paper/2506.13223/) (2025)
- [Best Agent Identification for General Game Playing](https://mlsanity.com/paper/2507.00451/) (2025)

## Abstract (arXiv)

This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression learning models to predict the performance of these heuristics based on each game's description file. We also provide a condensed analysis of the games available in Ludii, and the different ludemes that define them.