Over the last few years, much of game studies has focused on centering the player, and indeed this year the theme of this conference is celebrating the player. And yet, we are also seeing a fascinating body of work developing around the creation of bots, AIs, and procedural creations which might fairly be said to be centering the *played* instead. We are seeing the science of player modeling developing at a rapid rate, which might be termed the process of turning a player *into* the played. We’ve also seen, over the years, debates about ludology versus narratology. Debates about formalism and ontology and culture. Debates about play and rules, play and structure, play and game. We’ve heard that the game is the interface. That the interface is irrelevant…
It’s all rather tiring, isn’t it?
A ray of hope exists, however, in the fact that as digital literacy has risen, more and more people – practitioners, academics, critics, scholars – are comfortable moving across fields, and having consilient discussions. In this talk, I will discuss the cross-disciplinary approaches that have become my personal lodestones, as a practicing designer who is fascinated by systems and yet also regards the game designer’s actual canvas as being the human mind.
Mixed reality platforms enable people to interact with computers, the environment and each other, in more, better and surprising ways.
Obviously mixed reality (MR) platforms let people see and hear virtual things in the real world, but surprisingly MR could also accelerate machine learning and make computers more personal. Augmented reality platforms include additional and exotic sensors that gather an immense amount of information about users’ environments. Those platforms process that data to understand what users do and how they do it.
An exciting challenge and big benefit will be for machines to understand WHY users act, anticipate their needs and help them achieve more. Mixed reality platforms will give people new ways to interact with computers, the environment and each other.
Abstract
The panel on Machine Learning for Procedural Content Generation will expose the FDG audience to the emerging area of research around applying machine learning to content modeling, analysis, and generation. The panel will showcase the existing work in the eld, discuss current challenges, and highlight open opportunities for further research in the area. By exposing new ways for AI and machine learning to intersect with games we hope to encourage wider participation in this emerging domain and expose the FDG community to new techniques for studying games.