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Details of Grant 

EPSRC Reference: TS/G002835/1
Title: CAD-GAME: Computer-Aided Game Design
Principal Investigator: Colton, Professor S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Computing
Organisation: Imperial College London
Scheme: Technology Programme
Starts: 01 November 2008 Ends: 30 November 2011 Value (£): 327,955
EPSRC Research Topic Classifications:
Artificial Intelligence Computer Graphics & Visual.
Human-Computer Interactions
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
TS/G002843/1
Panel History:  
Summary on Grant Application Form
As a form of media - increasingly, mass media - games have much in common with film, particularly in terms of business models. One reason for the high levels of risk in film is that only limited market testing can be done prior to product release, and the product is essentially fixed from then on. Games have traditionally followed this model, but it is important to remember that games are not just media - they are also pieces of software. One major lesson from the software industry is that capturing users' interactions with a product can be used to refine market offerings in several ways: by adapting it after release (e.g. adaptive interfaces), by using that data to iteratively refine products in future releases (e.g. error reporting in Microsoft and Apple), and to understand the various user groups in more depth. In essence, we are suggesting that this approach can be directly applied to games. The difficulty, however, is that we cannot use simple measures of task completion, because there is no task: we are simply trying to entertain. The main research challenge is to understand better just what the word 'entertain' really means in games, and how this might be reflected in patterns of player behaviour. To do this, we will undertake a study of enjoyment and immersion in video games, in order to derive a concrete methodology for closely estimating the amount of enjoyment and immersion a player has, at fairly fine-grained intervals of a game. We will also capture a multitude of different forms of data from players actually playing Rebellion's games, and we will use advanced techniques from Artificial Intelligence to search for correlations with the player's overall enjoyment. These techniques could be used during design to speed up the process of tweaking the various game parameters - where the enemies are, how effective weapons are, etc. More interesting, however, is the idea that data analysis tools could run within the game itself, adapting the game in response to the player's behaviour. In this way, we hope to pioneer a new age of user-adaptive video games, within a one game, many gameplays paradigm, i.e., where each player has a unique game experience which is tailored to their personality, level of experience, playing style and mood.
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Organisation Website: http://www.imperial.ac.uk