Categorizing Morality Systems Through the Lens of Fallout

Morality systems in computer role-playing games (CRPGs) are a characteristic feature of the genre. Although there is plenty of literature studying how players relate to moral choices, only a few studies analyze or compare how specific games represent the player's moral persona. This paper studies how morality systems have been modeled in the Fallout series to keep track of the player's moral profile, categorizing the different techniques used in those systems. A special emphasis is put on how in-game actions affect the PC's moral alignment, as well as how non-player characters (NPCs) react to that beyond the game's scripted narrative. The goal is to provide guidelines that would lead to the development of more comprehensive and detailed morality systems, and where the player could immerse in a virtual world where the NPCs would act more as individual agents, with less reliance on explicitly scripted scenarios

Player Choices with Round Character Avatars

This study investigates the choices players make in a visual novel when faced with both an altruistic and narcissistic round avatar, where a round avatar is one with strong personality traits. Specifically, we examine whether players make choices that align with the avatar's personality or with the player's own personality, regardless of the avatar. In addition, we examine whether there is a change in behavior in the player after playing with avatars with different personality traits. Our study finds that players make choices that align with the avatar's personality when the player relates to the avatar; otherwise, players are inclined to make the choices that they believe will improve their avatar's relationship with other characters.M.S., Digital Media -- Drexel University, 201

Analysis of Human and Agent Characteristics on Human-Agent Team Performance and Trust

The human-agent team represents a new construct in how the United States Department of Defense is orchestrating mission planning and mission accomplishment. In order for mission planning and accomplishment to be successful, several requirements must be met: a firm understanding of human trust in automated agents, how human and automated agent characteristics influence human-agent team performance, and how humans behave. This thesis applies a combination of modeling techniques and human experimentation to understand the concepts aforementioned. The modeling techniques used include static modeling in SysML activity diagrams and dynamic modeling of both human and agent behavior in IMPRINT. Additionally, this research consisted of human experimentation in a dynamic, event-driven, teaming environment known as Space Navigator. Both the modeling and the experimenting depict that the agent\u27s reliability has a significant effect upon the human-agent team performance. Additionally, this research found that the age, gender, and education level of the human user has a relationship with the perceived trust the user has in the agent. Finally, it was found that patterns of compliant human behavior, archetypes, can be created to classify human users

Assessing Influential Users in Live Streaming Social Networks

abstract: Live streaming has risen to significant popularity in the recent past and largely this live streaming is a feature of existing social networks like Facebook, Instagram, and Snapchat. However, there does exist at least one social network entirely devoted to live streaming, and specifically the live streaming of video games, Twitch. This social network is unique for a number of reasons, not least because of its hyper-focus on live content and this uniqueness has challenges for social media researchers. Despite this uniqueness, almost no scientific work has been performed on this public social network. Thus, it is unclear what user interaction features present on other social networks exist on Twitch. Investigating the interactions between users and identifying which, if any, of the common user behaviors on social network exist on Twitch is an important step in understanding how Twitch fits in to the social media ecosystem. For example, there are users that have large followings on Twitch and amass a large number of viewers, but do those users exert influence over the behavior of other user the way that popular users on Twitter do? This task, however, will not be trivial. The same hyper-focus on live content that makes Twitch unique in the social network space invalidates many of the traditional approaches to social network analysis. Thus, new algorithms and techniques must be developed in order to tap this data source. In this thesis, a novel algorithm for finding games whose releases have made a significant impact on the network is described as well as a novel algorithm for detecting and identifying influential players of games. In addition, the Twitch network is described in detail along with the data that was collected in order to power the two previously described algorithms.Dissertation/ThesisDoctoral Dissertation Computer Science 201