Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial digital games. AI for non playing characters (NPC) in computer games tends to come from people with computing skills well beyond the average user. The
prime reason behind the lack of involvement of novice users in creating AI behaviors for NPC's in computer games is that construction of high quality AI behaviors is a hard problem. There are two reasons for it. First, creating a set of AI behavior requires specialized skills in design and programming. The nature of the process
restricts it to certain individuals who have a certain expertise in this area. There
is little understanding of how the behavior authoring process can be simplified with
easy-to-use authoring environments so that novice users (without programming and
design experience) can carry out the behavior authoring task. Second, the constructed
AI behaviors have problems and bugs in them which cause a break in player expe-
rience when the problematic behaviors repeatedly fail. It is harder for novice users
to identify, modify and correct problems with the authored behavior sets as they do
not have the necessary debugging and design experience. The two issues give rise to
a couple of interesting questions that need to be investigated: a) How can the AI
behavior construction process be simplified so that a novice user (without program-
ming and design experience) can easily conduct the authoring activity and b) How
can the novice users be supported to help them identify and correct problems with
the authored behavior sets?
In this thesis, I explore the issues related to the problems highlighted and propose
a solution to them within an application domain, named Second Mind(SM). In SM
novice users who do not have expertise in computer programming employ an authoring
interface to design behaviors for intelligent virtual characters performing a service
in a virtual world. These services range from shopkeepers to museum hosts. The
constructed behaviors are further repaired using an AI based approach. To evaluate
the construction and repair approach, we conduct experiments with human subjects.
Based on developing and evaluating the solution, I claim that a design solution
with behavior timeline based interaction design approach for behavior construction
supported by an understandable vocabulary and reduced feature representation for-
malism enables novice users to author AI behaviors in an easy and understandable
manner for NPCs performing a service in a virtual world. I further claim that an
introspective reasoning approach based on comparison of successful and unsuccessful
execution traces can be used as a means to successfully identify breaks in player ex-
perience and modify the failures to improve the experience of the player interacting
with NPCs performing a service in a virtual world. The work contributes in the
following three ways by providing: 1) a novel introspective reasoning approach for
successfully detecting and repairing failures in AI behaviors for NPCs performing a
service in a virtual world.; 2) a novice user understandable authoring environment to
help them create AI behaviors for NPCs performing a service in a virtual world in an
easy and understandable manner; and 3) Design, debugging and testing scaffolding
to help novice users modify their authored AI behaviors and achieve higher quality
modified AI behaviors compared to their original unmodified behaviors.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/42724 |
| Date | 19 August 2011 |
| Creators | Mehta, Manish |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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