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相关论文: Toward Game Level Generation from Gameplay Videos

200 篇论文

The ability to extract the sequence of game events for a given player's play-through has traditionally required access to the game's engine or source code. This serves as a barrier to researchers, developers, and hobbyists who might…

计算机视觉与模式识别 · 计算机科学 2018-09-18 Zijin Luo , Matthew Guzdial , Nicholas Liao , Mark Riedl

Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based methods have been applied to various content types such as…

人工智能 · 计算机科学 2020-10-12 Jialin Liu , Sam Snodgrass , Ahmed Khalifa , Sebastian Risi , Georgios N. Yannakakis , Julian Togelius

Procedural content generation (PCG) is of great interest to game design and development as it generates game content automatically. Motivated by the recent learning-based PCG framework and other existing PCG works, we propose an alternative…

人工智能 · 计算机科学 2015-11-03 Peizhi Shi , Ke Chen

This paper introduces a surrogate model of gameplay that learns the mapping between different game facets, and applies it to a generative system which designs new content in one of these facets. Focusing on the shooter game genre, the paper…

机器学习 · 计算机科学 2021-03-30 Daniel Karavolos , Antonios Liapis , Georgios N. Yannakakis

People enjoy encounters with generative software, but rarely are they encouraged to interact with, understand or engage with it. In this paper we define the term 'PCG-based game', and explain how this concept follows on from the idea of an…

人工智能 · 计算机科学 2016-10-12 Michael Cook , Mirjam Eladhari , Andy Nealen , Mike Treanor , Eddy Boxerman , Alex Jaffe , Paul Sottosanti , Steve Swink

This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content. As the importance of PCG for game development increases,…

An increasingly common area of study in procedural content generation is the creation of level segments: short pieces that can be used to form larger levels. Previous work has used basic concatenation to form these larger levels. However,…

人工智能 · 计算机科学 2022-08-23 Colan Biemer , Seth Cooper

In this paper, we present a method for automated persona-driven video game tutorial level generation. Tutorial levels are scenarios in which the player can explore and discover different rules and game mechanics. Procedural personas can…

人工智能 · 计算机科学 2022-04-12 Michael Cerny Green , Ahmed Khalifa , M Charity , Julian Togelius

We introduce the General Video Game Rule Generation problem, and the eponymous software framework which will be used in a new track of the General Video Game AI (GVGAI) competition. The problem is, given a game level as input, to generate…

人工智能 · 计算机科学 2019-06-13 Ahmed Khalifa , Michael Cerny Green , Diego Perez-Liebana , Julian Togelius

The design of video game levels is a complex and critical task. Levels need to elicit fun and challenge while avoiding frustration at all costs. In this paper, we present a framework to assist designers in the creation of levels for 2D…

人工智能 · 计算机科学 2018-04-25 Antonio Umberto Aramini , Pier Luca Lanzi , Daniele Loiacono

Procedural content generation via machine learning (PCGML) is the process of procedurally generating game content using models trained on existing game content. PCGML methods can struggle to capture the true variance present in underlying…

机器学习 · 计算机科学 2021-07-28 Bowei Li , Ruohan Chen , Yuqing Xue , Ricky Wang , Wenwen Li , Matthew Guzdial

Recent years, there has been growing interests in experience-driven procedural level generation. Various metrics have been formulated to model player experience and help generate personalised levels. In this work, we question whether…

人工智能 · 计算机科学 2022-07-06 Keyuan Zhang , Jiayu Bai , Jialin Liu

We address the problem of game level repair, which consists of taking a designed but non-functional game level and making it functional. This might consist of ensuring the completeness of the level, reachability of objects, or other…

人工智能 · 计算机科学 2025-06-25 Debosmita Bhaumik , Julian Togelius , Georgios N. Yannakakis , Ahmed Khalifa

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

计算机视觉与模式识别 · 计算机科学 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

This project proposes a methodology for the automatic generation of action models from video game dynamics descriptions, as well as its integration with a planning agent for the execution and monitoring of the plans. Planners use these…

人工智能 · 计算机科学 2021-09-08 Ignacio Vellido , Carlos Núñez-Molina , Vladislav Nikolov , Juan Fdez-Olivares

Recent advancements in procedural content generation via machine learning enable the generation of video-game levels that are aesthetically similar to human-authored examples. However, the generated levels are often unplayable without…

This paper introduces the unsupervised learning problem of playable video generation (PVG). In PVG, we aim at allowing a user to control the generated video by selecting a discrete action at every time step as when playing a video game. The…

计算机视觉与模式识别 · 计算机科学 2021-01-29 Willi Menapace , Stéphane Lathuilière , Sergey Tulyakov , Aliaksandr Siarohin , Elisa Ricci

Large Language Models (LLMs) are powerful tools, capable of leveraging their training on natural language to write stories, generate code, and answer questions. But can they generate functional video game levels? Game levels, with their…

人工智能 · 计算机科学 2023-06-02 Graham Todd , Sam Earle , Muhammad Umair Nasir , Michael Cerny Green , Julian Togelius

Procedural content generation (PCG) is a growing field, with numerous applications in the video game industry and great potential to help create better games at a fraction of the cost of manual creation. However, much of the work in PCG is…

Machine learning advances have afforded an increase in algorithms capable of creating art, music, stories, games, and more. However, it is not yet well-understood how machine learning algorithms might best collaborate with people to support…