mlsanityData to 14 Oct 2026

Usando LLMs para Programar Jogos de Tabuleiro e Variacc~oes

arXiv 2511.05114 ↗First posted 7 Nov 2025cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for board games, as well as new variants of existing games.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 9 references that are in the map. First posted on arXiv 7 Nov 2025.

Builds on

6 of 9 references.

References · 6

  1. 2024A Performance Study of LLM-Generated Code on Leetcodecited by 49
  2. 2019Ludii -- The Ludemic General Game Systemcited by 39
  3. 2024GAVEL: Generating Games Via Evolution and Language Modelscited by 24
  4. 2024Grammar-based Game Description Generation using Large Language Modelscited by 7
  5. 2025Boardwalk: Towards a Framework for Creating Board Games with LLMscited by 2
  6. 2023Evolutionary Tabletop Game Design: A Case Study in the Risk Gamecited by 1

Built on by

Not cited yet.