Creating Engaging Artificial Characters for Games
Sweetser, Penelope, Johnson, Daniel M., Sweetser, Jane, & Wiles, Janet (2003) Creating Engaging Artificial Characters for Games. In Second Annual International Conference on Entertainment Computing (ICEC), 2003, Pittsburgh, Pennsylvania.
Game developers and researchers aim to model human behaviour in order to create more engaging, entertaining and satisfying artificial characters for computer games. It is a popular belief that intelligent behaviour is the key to creating better game AI. However, as yet there is no empirical evidence to support this theory or to indicate whether other attributes, such as social interaction, realistic behaviour and communication, should also be considered. This study aimed to find out which attributes people desire in team members and opponents in computer games. The study employed a questionnaire, administered to a group of university students, directed towards ascertaining the importance of different aspects of player behaviour in games. It was found that there are two different, non-homogenous groups, each with separate needs and wants that game developers should consider. Firstly, it was found that people who prefer playing computer games with other humans tend to value intelligent behaviour and social interaction more than people who prefer computer players. Secondly, it was found that people who prefer computer players do so for convenience, practice and a preference for games that can only be played individually. It is recommended that game developers should aim to model intelligent behaviour for the first group and that the second group require an in-game learning environment for skill-development.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Virtual Reality and Related Simulation (080111)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2003 (please consult author)|
|Deposited On:||28 Mar 2007|
|Last Modified:||10 Aug 2011 18:19|
Repository Staff Only: item control page