Procedural Content Generation via Machine Learning: An Overview

Author:   Matthew Guzdial ,  Sam Snodgrass ,  Adam J. Summerville
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2022
ISBN:  

9783031167218


Pages:   238
Publication Date:   07 December 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Procedural Content Generation via Machine Learning: An Overview


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Author:   Matthew Guzdial ,  Sam Snodgrass ,  Adam J. Summerville
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Weight:   0.433kg
ISBN:  

9783031167218


ISBN 10:   303116721
Pages:   238
Publication Date:   07 December 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Matthew Guzdial, Ph.D, is an Assistant Professor in the Computing Science Department at the University of Alberta and a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). His research focuses on the intersection of machine learning, creativity, and human-centered computing. He is a recipient of an Early Career Researcher Award from NSERC, a Unity Graduate Fellowship, and two best conference paper awards from the International Conference on Computational Creativity. His work has been featured in the BBC, WIRED, Popular Science, and Time. Sam Snodgrass is an AI researcher at modl.ai, a game AI company focused on bringing state of the art game AI research from academia to the games industry. His research focuses on making PCGML more accessible to non-ML experts. This work includes making PCGML systems more adaptable and self-reliant, reducing the authorial burden of creating training data through domain blending, and building tools that allow for easier interactions with the underlying PCGML systems and their outputs. Through his work at modl.ai he has deployed several mixed-initiative PCGML tools into game studios to assist with level design and creation. Adam Summerville is the lead AI engineer for Procedural Content Generation at The Molasses Flood, a CD Projekt studio. Prior to this, he was an assistant professor at California State Polytechnic University, Pomona. His research focuses on the intersection of artificial intelligence in games with a high-level goal of enabling experiences that would not be possible without artificial intelligence. This research ranges from procedural generation of levels, social simulation for games, and the use of natural language processing for gameplay. His work has been shown at the SF MoMA and SlamDance and won the audience choice award at IndieCade.

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