A data-driven approach for personalized drama management

An interactive narrative is a form of digital entertainment in which players can create or influence a dramatic storyline through actions, typically by assuming the role of a character in a fictional virtual world. The interactive narrative systems usually employ a drama manager (DM), an omniscient background agent that monitors the fictional world and determines what will happen next in the players' story experience. Prevailing approaches to drama management choose successive story plot points based on a set of criteria given by the game designers. In other words, the DM is a surrogate for the game designers. In this dissertation, I create a data-driven personalized drama manager that takes into consideration players' preferences. The personalized drama manager is capable of (1) modeling the players' preference over successive plot points from the players' feedback; (2) guiding the players towards selected plot points without sacrificing players' agency; (3) choosing target successive plot points that simultaneously increase the player's story preference ratings and the probability of the players selecting the plot points. To address the first problem, I develop a collaborative filtering algorithm that takes into account the specific sequence (or history) of experienced plot points when modeling players' preferences for future plot points. Unlike the traditional collaborative filtering algorithms that make one-shot recommendations of complete story artifacts (e.g., books, movies), the collaborative filtering algorithm I develop is a sequential recommendation algorithm that makes every successive recommendation based on all previous recommendations. To address the second problem, I create a multi-option branching story graph that allows multiple options to point to each plot point. The personalized DM working in the multi-option branching story graph can influence the players to make choices that coincide with the trajectories selected by the DM, while gives the players the full agency to make any selection that leads to any plot point in their own judgement. To address the third problem, the personalized DM models the probability that the players transitioning to each full-length stories and selects target stories that achieve the highest expected preference ratings at every branching point in the story space. The personalized DM is implemented in an interactive narrative system built with choose-your-own-adventure stories. Human study results show that the personalized DM can achieve significantly higher preference ratings than non-personalized DMs or DMs with pre-defined player types, while preserve the players' sense of agency.Ph.D

Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability

Personalization can be addressed by adaptability and adaptivity, which have different advantages and disadvantages. This study investigates how digital library users react to these two techniques. More specifically, we develop a personalized digital library to suit the needs of different cognitive styles based on the findings of our previous work (Frias-Martinez, et al., in press). The personalized digital library includes two versions: adaptive version and adaptable version. The results showed that users not only performed better in the adaptive version, but also they perceived more positively to the adaptive version. In addition, cognitive styles have great effects on users’ responses to adaptability and adaptivity. These results provide guidance for designers to select suitable techniques to develop personalized digital libraries

Understanding patterns of library use among undergraduate students from different disciplines

Objective The objective of this study was to test whether routinely-generated library usage data could be linked with information about students to understand patterns of library use among students from different disciplines at the University of Huddersfield. This information is important for librarians seeking to demonstrate the value of the library, and to ensure that they are providing services which meet user needs. The study seeks to join two strands of library user research which until now have been kept rather separate – an interest in disciplinary differences in usage, and a methodology which involves large-scale routinely-generated data. Methods The study uses anonymised data about individual students derived from two sources: routinely-generated data on various dimensions of physical and electronic library resource usage, and information from the student registry on the course studied by each student. Courses were aggregated at a subject and then disciplinary level. Kruskal-Wallis and Mann Whitney tests were used to identify statistically significant differences between the high-level disciplinary groups, and within each disciplinary group at the subject level. Results The study identifies a number of statistically significant differences on various dimensions of usage between both high-level disciplinary groupings and lower subject-level groupings. In some cases, differences are not the same as those observed in earlier studies, reflecting distinctive usage patterns and differences in the way that disciplines or subjects are defined and organised. Arts students at Huddersfield use library resources less than those in social science disciplines, contradicting findings from studies at other institutions, although music students are high users within the arts subject-level grouping. Computing and engineering students were relatively similar, although computing students were more likely to download PDFs, and engineering students were more likely to use the physical library. Conclusions The technique introduced in this study represents an effective way of understanding distinctive usage patterns at an individual institution. There may be potential to aggregate findings across several institutions to help universities benchmark their own performance and usage; this would require a degree of collaboration and standardisation. This study found that students in certain disciplines at Huddersfield use the library in different ways to students in those same disciplines at other institutions: further investigation is needed to understand exactly why these differences exist, but some hypotheses are offered

Museum Experience Design: A Modern Storytelling Methodology

In this paper we propose a new direction for design, in the context of the theme “Next Digital Technologies in Arts and Culture”, by employing modern methods based on Interaction Design, Interactive Storytelling and Artificial Intelligence. Focusing on Cultural Heritage, we propose a new paradigm for Museum Experience Design, facilitating on the one hand traditional visual and multimedia communication and, on the other, a new type of interaction with artefacts, in the form of a Storytelling Experience. Museums are increasingly being transformed into hybrid spaces, where virtual (digital) information coexists with tangible artefacts. In this context, “Next Digital Technologies” play a new role, providing methods to increase cultural accessibility and enhance experience. Not only is the goal to convey stories hidden inside artefacts, as well as items or objects connected to them, but it is also to pave the way for the creation of new ones through an interactive museum experience that continues after the museum visit ends. Social sharing, in particular, can greatly increase the value of dissemination

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications