Believable exploration : investigating human exploration behavior to inform the design of believable agents in video games

Publication Type:
Thesis
Issue Date:
2017
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By nature, human beings are curious about their environment. Arriving in a new place, they observe, recognize and interact with their surroundings. People collect information about the new place, and locate objects in that space that help them to make further decisions. This is a typical scenario of spatial exploration. Spatial exploration is common human behavior, where humans explore unknown environments to acquire information and resources. It is pervasively seen in real-world and virtual environments, from exploring new living/working spaces to charting the oceans or venturing beyond the boundaries of our planet. Just as humans explore ‘real’ environments, they also investigate artificial environments in video games. Computer agents, which perceive surrounding environments with limited visual range, often appear in exploration activities, acting as tools or partners for explorers. Despite the broad range of human activities that employ exploration behavior, this element has been insufficiently investigated and understood. Additionally, even though it is commonly accepted that believable agents benefit people in human-computer interaction systems, the research into creating computer agents with believable exploration behavior has been neglected. To solve these issues, I extract the patterns of human exploration behavior in virtual environments, and explore the methodologies of developing believable agents, which explore spatial environments in human-like ways. In the pursuit of this goal, this thesis makes the following four contributions to the emerging field of believable agent exploration: 1) I employed video games as a testbed to investigate human behavior of spatial exploration. Human players played specialized exploration games, verbalized their behavior during playing and discussed their thoughts in the post-play interview. Behavioral patterns were extracted based on replays of playing, think-aloud data and interview data via thematic analysis. 2) Differences of exploration behavior between human and computer agents were identified through a third-person-observation assessment of believability. 3) A heuristic agent was developed, which mimics human exploration methods reflected via the behavioral patterns. Three heuristics, as components of the heuristic agent, were designed to filter potential options when the agent decides where to explore in each step. 4) An integrated agent was developed by filling the behavior gaps between human and computer agents, where an integrated architecture embedded expectations of human-like exploration from mid-level players. Both the heuristic agent and the integrated agent passed the third-person-observation assessment of believability. Therefore, findings in this thesis contribute to fill the gaps in the fields of understanding human exploration behavior as well as developing believable agent.
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