Results 21 to 30 of about 148,368 (325)

PCGRL: Procedural Content Generation via Reinforcement Learning [PDF]

open access: yesProceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2020
We investigate how reinforcement learning can be used to train level-designing agents. This represents a new approach to procedural content generation in games, where level design is framed as a game, and the content generator itself is learned.
A. Khalifa   +3 more
semanticscholar   +3 more sources

Exploring Procedural Content Generation of Environments for Virtual Museums: A Mixed-Initiative Approach

open access: goldHeritage
Cultural heritage preservation and dissemination face significant challenges in the digital era, particularly in artifact representation, visitor experience personalization, and virtual exploration scalability.
Claudio Rubio   +4 more
openalex   +3 more sources

Experience-Driven Procedural Content Generation [PDF]

open access: greenIEEE Transactions on Affective Computing, 2011
Procedural content generation (PCG) is an increasingly important area of technology within modern human-computer interaction (HCI) design. Personalization of user experience via affective and cognitive modeling, coupled with real-time adjustment of the content according to user needs and preferences are important steps toward effective and meaningful ...
Georgios N. Yannakakis, Julian Togelius
openalex   +3 more sources

PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning [PDF]

open access: greenarXiv.org
Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, several studies have explored reward generation for training game agents and controlling robots using large
In-Chang Baek   +6 more
openalex   +2 more sources

Procedural Content Generation via Machine Learning (PCGML) [PDF]

open access: greenIEEE Transactions on Games, 2018
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, researchers explore new avenues for generating high-quality content with or without human involvement; this paper ...
Adam Summerville   +7 more
openalex   +5 more sources

Game Balance Through Procedural Content Generation

open access: bronzeInternational Conference on Foundations of Digital Games
This preliminary work explores procedural content generation as a method for improving game balance. Traditionally, achieving balance requires designers to fine-tune parameters to ensure interactions between game elements promotes equitable gameplay ...
Mathias Babin, Michael Katchabaw
openalex   +2 more sources

Procedural Generation in Games: Focusing on Dungeons [PDF]

open access: yesSHS Web of Conferences, 2022
This report is talking about the applications of procedural generation in games. There are many AI-generated games on the market, such as No Man’s Sky.
Shen Zhenyuan
doaj   +1 more source

Procedural Content Generation via Knowledge Transformation (PCG-KT) [PDF]

open access: yesIEEE Transactions on Games, 2023
In this article, we introduce the concept of procedural content generation via knowledge transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which content generation is enabled by the process of knowledge ...
Anurag Sarkar   +5 more
semanticscholar   +1 more source

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