Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/81202
Title: Mixed-media game AI
Authors: André, Elizabeth
Bakkes, Sander
Bidarra, Rafael
Dahlskog, Steve
Palosari Eladhari, Mirjam
Paiva, Ana
Preuss, Mike
Smith, Gillian
Sullivan, Anne
Thompson, Tommy
Thue, David
Yannakakis, Georgios N.
Young, Michael R.
Liapis, Antonios
Keywords: Artificial intelligence
Machine learning
Computer games -- Design
Computer games -- Programming
Issue Date: 2018
Publisher: Schloss Dagstuhl Leibniz-Zentrum für Informatik GmbH
Citation: Liapis, A., Dahlskog, S., Eladhari, M. P.,Paiva, A., Preuss, M., Smith, G.,…Young, R. M. (2018). Mixed-media game AI. Dagstuhl Reports, 7(11), 105-107.
Abstract: Over the last decades, digital technologies have moved away from the personal computer (PC) into cloud computing, ubiquitous computing, intelligent robots and smart devices. From wearable technologies to remote-controlled household items and from sensors for crowd control to personal drones, there is a broad range of sources which can be exploited for artificial intelligence in games. While artificial intelligence (AI) is already a big part of the Internet of Things, raising concerns in terms of ethics and politics, games have been relatively partitioned away to PCs. Relevant work on wearable technologies as game controllers, mixed- or virtual-reality rendering, or technology-enhanced play in playgrounds, social robots for games or board games, has largely not taken advantage of artificial intelligence for controlling or mediating the experience. Using the term mixed-media to refer broadly to any media, digital or otherwise, outside the game data within a PC or a game-specific database, this working group attempted to map out the broad topic of mixed-media in terms of its applications for game AI.
URI: https://www.um.edu.mt/library/oar/handle/123456789/81202
Appears in Collections:Scholarly Works - InsDG

Files in This Item:
File Description SizeFormat 
Mixed-media_game_AI_2018.pdf100.23 kBAdobe PDFView/Open


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.