Date of Award

Fall 12-20-2019

Degree Type

Thesis

Degree Name

M.S.

Degree Program

Computer Science

Department

Computer Science

Major Professor

Stephen G Ware

Second Advisor

Md Tamjidul Hoque

Third Advisor

Ben Samuel

Abstract

In this thesis I describe a method where an experience manager chooses actions for non-player characters (NPCs) in intelligent interactive narratives through story graph representation and pruning. The space of all stories can be represented as a story graph where nodes are states and edges are actions. By shaping the domain as a story graph, experience manager decisions can be made by pruning edges. Starting with a full graph, I apply a set of pruning strategies that will allow the narrative to be finishable, NPCs to act believably, and the player to be responsible for how the story unfolds. By never pruning player actions, the experience manager can accommodate any player choice. This experience management technique was first implemented on a training simulation, where participants’ performance improved over repeated sessions. This technique was also employed on an adventure game where players generally found the NPCs’ behaviors to be more believable than the control.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.

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