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This paper presents a novel framework for automated game template generation by transforming Game Design Documents (GDDs) into functional Unity game prototypes using Natural Language Processing (NLP) and multi-modal Large Language Models…

人工智能 · 计算机科学 2025-09-12 Amna Hassan

This paper investigates how the integration of large language models influences gameplay, playability, and player experience in game development. We report a collaborative autoethnographic study of two game projects in which LLMs were…

软件工程 · 计算机科学 2026-03-31 Keeryn Johnson , Muhammad Ahmed , Charlie Lang , Sahib Thethi , Wilson Zheng , Ronnie de Souza Santos

Traditional ontologies describe domain structure but cannot generate novel artifacts. Large language models generate fluently but produce outputs lacking structural validity, hallucinating mechanisms without components, goals without end…

人工智能 · 计算机科学 2026-02-10 Benny Cheung

Large Language Models (LLMs) have shown great ability in generating executable code from natural language, opening the possibility of automatically constructing environments for AI agents. Recent work on Code World Models (CWMs)…

人工智能 · 计算机科学 2026-05-26 Tyrone Serapio , Arjun Prakash , Haoyang Xu , Kevin Wang , Amy Greenwald

We present a novel architecture for safely integrating Large Language Models (LLMs) into interactive game engines, allowing players to "program" new behaviors using natural language. Our framework mitigates risks by using an LLM to…

人机交互 · 计算机科学 2025-10-21 Austin Drake , Hang Dong

Large Language Models (LLMs) reasoning abilities are increasingly being applied to classical board and card games, but the dominant approach -- involving prompting for direct move generation -- has significant drawbacks. It relies on the…

This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to operate within formally specified, rule-governed environments. We evaluate four LLMs (Gemini 2.5 Pro and…

人工智能 · 计算机科学 2026-02-24 Maciej Świechowski , Adam Żychowski , Jacek Mańdziuk

Large Language Models (LLMs) are increasingly deployed in real-world applications that demand complex reasoning. To track progress, robust benchmarks are required to evaluate their capabilities beyond superficial pattern recognition.…

计算与语言 · 计算机科学 2025-06-03 Wenye Lin , Jonathan Roberts , Yunhan Yang , Samuel Albanie , Zongqing Lu , Kai Han

Large language models (LLMs) have taken the scientific world by storm, changing the landscape of natural language processing and human-computer interaction. These powerful tools can answer complex questions and, surprisingly, perform…

人工智能 · 计算机科学 2023-11-14 Pier Luca Lanzi , Daniele Loiacono

Implementing board games in code can be a time-consuming task. However, Large Language Models (LLMs) have been proven effective at generating code for domain-specific tasks with simple contextual information. We aim to investigate whether…

Game designs often center on the game mechanics---rules governing the logical evolution of the game. We seek to develop an intelligent system that generates computer games. As first steps towards this goal we present a composable and…

人工智能 · 计算机科学 2019-08-06 Alexander Zook , Mark O. Riedl

There is a broad consensus that the inability to form long-term plans is one of the key limitations of current foundational models and agents. However, the existing planning benchmarks remain woefully inadequate to truly measure their…

人工智能 · 计算机科学 2026-04-07 Michael Katz , Harsha Kokel , Sarath Sreedharan

The large language model (LLM) based agents have demonstrated their capacity to automate and expedite software development processes. In this paper, we focus on game development and propose a multi-agent collaborative framework, dubbed…

人工智能 · 计算机科学 2025-09-09 Dake Chen , Haoyang Zhang , Hanbin Wang , Yunhao Huo , Yuzhao Li , Junjie Wang

Large language models (LLMs) excel at processing and generating both text and code. However, LLMs have had limited applicability in grounded task-oriented dialogue as they are difficult to steer toward task objectives and fail to handle…

计算与语言 · 计算机科学 2023-10-27 Justin T. Chiu , Wenting Zhao , Derek Chen , Saujas Vaduguru , Alexander M. Rush , Daniel Fried

Recent advances in large language models (LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in procedural content generation (PCG). We present a lightweight…

图形学 · 计算机科学 2026-01-05 Yi-Chun Chen , Arnav Jhala

Large language models (LLMs) offer promise for dynamic game content generation, but they face critical barriers, including narrative incoherence and high operational costs. Due to their large size, they are often accessed in the cloud,…

人工智能 · 计算机科学 2026-05-20 Morten I. K. Munk , Arturo Valdivia , Paolo Burelli

We present RPGBench, the first benchmark designed to evaluate large language models (LLMs) as text-based role-playing game (RPG) engines. RPGBench comprises two core tasks: Game Creation (GC) and Game Simulation (GS). In GC, an LLM must…

计算与语言 · 计算机科学 2025-02-04 Pengfei Yu , Dongming Shen , Silin Meng , Jaewon Lee , Weisu Yin , Andrea Yaoyun Cui , Zhenlin Xu , Yi Zhu , Xingjian Shi , Mu Li , Alex Smola

Introduction: As digital games grow in complexity, the role of the Game Producer becomes increasingly relevant for aligning creative, technical, and business dimensions. Objective: This study aimed to identify and map the main…

软件工程 · 计算机科学 2025-06-18 Rafael C. Lopes , Danilo M. Ribeiro

We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired by James P. Carse's distinction between finite and infinite…

计算机视觉与模式识别 · 计算机科学 2024-10-31 Jialu Li , Yuanzhen Li , Neal Wadhwa , Yael Pritch , David E. Jacobs , Michael Rubinstein , Mohit Bansal , Nataniel Ruiz

As Large Language Models (LLMs) are integrated into critical real-world applications, their strategic and logical reasoning abilities are increasingly crucial. This paper evaluates LLMs' reasoning abilities in competitive environments…

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