| Type of Document |
Master's Thesis |
| Author |
Harris, Justin Tucker, |
| URN |
etd-11012005-075353 |
| Title |
Proactive Mediation in Plan-Based Narrative Environments |
| Degree |
Master of Science |
| Graduate Program |
Computer Science |
| Advisory Committee |
| Advisor Name |
Title |
| R. Michael Young |
Committee Chair |
| James Lester |
Committee Member |
| Jon Doyle |
Committee Member |
|
| Keywords |
- Interactive Narrative
- Human-Computer Interaction
- Artificial Intelligence
|
| Date of Defense |
2005-10-24 |
| Availability |
unrestricted |
Abstract
In interactive plan-based narrative environments, user's actions must be monitored to ensure that conditions necessary for the execution of narrative plans are not compromised. In the Zocalo system, management of user actions is performed on a reactionary basis by a process called mediation. In this thesis, an extension to this approach, proactive mediation, is described, which calculates responses to user input in an anticipatory manner. A proactive mediation module accepts as input a plan describing the actions being performed by the user (generated by a plan recognition system) and identifies portions of that plan that jeopardize the causal structure of the overall narrative. Once these portions are identified, proactive mediation generates modifications to the narrative plan structure that avoid the unwanted interaction between user and story. This extension to the original mediation algorithm provides more responses to a user's actions and generates responses that are more tailored to the user's actions.
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| Files |
| Filename |
Size |
Approximate Download Time
(Hours:Minutes:Seconds)
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| 28.8 Modem |
56K Modem |
ISDN (64 Kb) |
ISDN (128 Kb) |
Higher-speed Access |
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etd.pdf |
1.64 Mb |
00:07:36 |
00:03:54 |
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