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Generative Adversarial Networks (GANs) are an emerging form of indirect encoding. The GAN is trained to induce a latent space on training data, and a real-valued evolutionary algorithm can search that latent space. Such Latent Variable…

神经与进化计算 · 计算机科学 2020-04-02 Jacob Schrum , Jake Gutierrez , Vanessa Volz , Jialin Liu , Simon Lucas , Sebastian Risi

We present Word2Minecraft, a system that leverages large language models to generate playable game levels in Minecraft based on structured stories. The system transforms narrative elements-such as protagonist goals, antagonist challenges,…

计算与语言 · 计算机科学 2025-03-24 Shuo Huang , Muhammad Umair Nasir , Steven James , Julian Togelius

We present latent combinational game design -- an approach for generating playable games that blend a given set of games in a desired combination using deep generative latent variable models. We use Gaussian Mixture Variational Autoencoders…

机器学习 · 计算机科学 2023-12-22 Anurag Sarkar , Seth Cooper

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

We present a new method of automatic critical mechanic discovery for video games using a combination of game description parsing and playtrace information. This method is applied to several games within the General Video Game Artificial…

人工智能 · 计算机科学 2020-09-16 Michael Cerny Green , Ahmed Khalifa , Gabriella A. B. Barros , Tiago Machado , Julian Togelius

In this article, we present an experimental approach to using parameterized Generative Adversarial Networks (GANs) to produce levels for the puzzle game Lily's Garden. We extract two condition vectors from the real levels in an effort to…

人工智能 · 计算机科学 2023-06-29 Andreas Hald , Jens Struckmann Hansen , Jeppe Kristensen , Paolo Burelli

Large Language Models (LLMs) have proven to be useful tools in various domains outside of the field of their inception, which was natural language processing. In this study, we provide practical directions on how to use LLMs to generate…

计算与语言 · 计算机科学 2023-07-04 Muhammad U Nasir , Julian Togelius

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

Procedural Content Generation via Machine Learning (PCGML) has enhanced game content creation, yet challenges in controllability and limited training data persist. This study addresses these issues by distilling a constructive PCG algorithm…

We propose a new General Game Playing (GGP) system called Regular Games (RG). The main goal of RG is to be both computationally efficient and convenient for game design. The system consists of several languages. The core component is a…

人工智能 · 计算机科学 2025-11-14 Radosław Miernik , Marek Szykuła , Jakub Kowalski , Jakub Cieśluk , Łukasz Galas , Wojciech Pawlik

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…

Automated game design (AGD), the study of automatically generating game rules, has a long history in technical games research. AGD approaches generally rely on approximations of human play, either objective functions or AI agents. Despite…

人工智能 · 计算机科学 2023-10-06 Johor Jara Gonzalez , Seth Cooper , Matthew Guzdial

In recent years, Artificial Intelligence Generated Content (AIGC) has advanced from text-to-image generation to text-to-video and multimodal video synthesis. However, generating playable games presents significant challenges due to the…

人工智能 · 计算机科学 2024-12-03 Mingyu Yang , Junyou Li , Zhongbin Fang , Sheng Chen , Yangbin Yu , Qiang Fu , Wei Yang , Deheng Ye

Deceptive games are games where the reward structure or other aspects of the game are designed to lead the agent away from a globally optimal policy. While many games are already deceptive to some extent, we designed a series of games in…

人工智能 · 计算机科学 2018-02-06 Damien Anderson , Matthew Stephenson , Julian Togelius , Christian Salge , John Levine , Jochen Renz

Procedural Content Generation (PCG) is a technique to generate complex and diverse environments in an automated way. However, while generating content with PCG methods is often straightforward, generating meaningful content that reflects…

Real-time global illumination is key to enabling more dynamic and physically realistic worlds in performance-critical applications such as games or any other applications with real-time constraints.Hardware-accelerated ray tracing in modern…

Automatically generating novel and interesting games is a complex task. Challenges include representing game rules in a computationally workable form, searching through the large space of potential games under most such representations, and…

We present a comparative study of methods for generating realistic, constrained small- to medium-scale road networks with built-in redundancy. In this research, we evaluate the proposed Evolutionary Algorithm (EA) with connectivity and…

神经与进化计算 · 计算机科学 2026-03-24 Artur Morys-Magiera , Marek Długosz , Paweł Skruch

Game balancing is an important part of the (computer) game design process, in which designers adapt a game prototype so that the resulting gameplay is as entertaining as possible. In industry, the evaluation of a game is often based on…

人机交互 · 计算机科学 2016-03-15 Vanessa Volz , Günter Rudolph , Boris Naujoks

Differential MAP-Elites is a novel algorithm that combines the illumination capacity of CVT-MAP-Elites with the continuous-space optimization capacity of Differential Evolution. The algorithm is motivated by observations that illumination…

神经与进化计算 · 计算机科学 2021-07-13 Tae Jong Choi , Julian Togelius