Usando LLMs para Programar Jogos de Tabuleiro e Variações

2025/11/07 by Becker, Álvaro Guglielmin, Rossato, Lana Bertoldo, Tavares, Anderson Rocha
Computer Science · Psychology · #Artificial Intelligence in Games #Educational Games and Gamification #FOS: Computer and information sciences #Machine Learning (cs.LG) #Text Readability and Simplification

paper · doi:10.48550/arxiv.2511.05114

openalex publication_date 2025/11/07 · openalex created_date 2025/11/11 · openalex updated_date 2026/07/28

Abstract

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.

Citations

• Boardwalk: Towards a Framework for Creating Board Games with LLMs
• GAVEL: Generating Games Via Evolution and Language Models
• Ludii -- The Ludemic General Game System

Related

• Boardwalk: Towards a Framework for Creating Board Games with LLMs
• Diamonds in the rough: Transforming SPARCs of imagination into a game concept by leveraging medium sized LLMs
• Large Language Models and Games: A Survey and Roadmap
• From Code to Play: Benchmarking Program Search for Games Using Large Language Models
• Evaluating Large Language Models with Grid-Based Game Competitions: An Extensible LLM Benchmark and Leaderboard