Role Playing Learning for Socially Concomitant Mobile Robot Navigation

In this paper, we present the Role Playing Learning (RPL) scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks (NN) are constructed to parameterize a stochastic policy that directly maps sensory data collected by the robot to its velocity outputs, while respecting a set of social norms. An efficient simulative learning environment is built with maps and pedestrians trajectories collected from a number of real-world crowd data sets. In each learning iteration, a robot equipped with the NN policy is created virtually in the learning environment to play itself as a companied pedestrian and navigate towards a goal in a socially concomitant manner. Thus, we call this process Role Playing Learning, which is formulated under a reinforcement learning (RL) framework. The NN policy is optimized end-to-end using Trust Region Policy Optimization (TRPO), with consideration of the imperfectness of robot's sensor measurements. Simulative and experimental results are provided to demonstrate the efficacy and superiority of our method

Youth and Digital Media: From Credibility to Information Quality

Building upon a process-and context-oriented information quality framework, this paper seeks to map and explore what we know about the ways in which young users of age 18 and under search for information online, how they evaluate information, and how their related practices of content creation, levels of new literacies, general digital media usage, and social patterns affect these activities. A review of selected literature at the intersection of digital media, youth, and information quality -- primarily works from library and information science, sociology, education, and selected ethnographic studies -- reveals patterns in youth's information-seeking behavior, but also highlights the importance of contextual and demographic factors both for search and evaluation. Looking at the phenomenon from an information-learning and educational perspective, the literature shows that youth develop competencies for personal goals that sometimes do not transfer to school, and are sometimes not appropriate for school. Thus far, educational initiatives to educate youth about search, evaluation, or creation have depended greatly on the local circumstances for their success or failure

Gamifying Navigation in Location-Based Applications

Location-based games entertain players usually by interactions at points of interest (POIs). Navigation between POIs often involve the use of either a physical or digital map, not taking advantage of the opportunity available to engage users in activities between POIs. The paper presents riddle solving as a navigational method for a location-based game. 10 families with 2-6 persons and at least one child in the age range 9- 11 years old participated in the evaluation. Results show that riddle solving as a navigational method is more enjoyable than a 2D digital map. Additional findings from video recordings, field notes, questionnaires, logging and semi-structured interviews revealed that riddle solving has potential for engaging users in learning activities

Perception of space through representation media: a comparison between 2D representation techniques and 3D virtual environments

Thesis (Master)--İzmir Institute of Technology, Architecture, İzmir, 2005Includes bibliographical references (leaves: 109-113)Text in English; Abstract: Turkish and Englishxii, 122 leavesFor centuries, 2D drawing techniques such as plans, sections and elevations have been the main communication media for the profession of architecture. Addition to these techniques, for two decades, computer based representation techniques and 3D virtual environments (VE) have also entered to the profession of architecture. Effects of these computer based techniques on perception of space have always been interrogated by several researches.Although these researches generally regarded these computerized techniques as better and proper than conventional techniques, in some cases conventional techniques can be more effective to depict architectural space. Main aim of this thesis is to compare and evaluate the positive effects and shortcomings of 3D virtual environments and 2D conventional representation techniques in the context of perception of architectural space. Parallel to this objective, the thesis also aims to show the differentiation in perception of space with the change of representation media. To show these differences, a comparative method is used. As the main step of the application of this method, an experimental case study and survey has been constituted for comparing 2D conventional techniques and 3D computer based techniques. In this survey, 38 first yearstudents from Izmir Institute of technology have taken place as test subject.According to the results of this comparative case study, contributions and shortcomings of 2D conventional representation techniques and 3D computer based techniques on improving the capability of architects on perception of the space have been determined

REDUCING THE COGNITIVE LOAD OF DECISION-MAKERS IN EMERGENCY MANAGEMENT THROUGH AUGMENTED REALITY

Decision processes in emergency management are particularly complex. Operations managers have to make decisions under time pressure while the situation at hand changes continuously. As wrong decisions in emergencies often have drastic effects, operations managers try to receive information from various sources such as the emergency control centre, their operation forces, databases, electronic location maps and drones. However, previous research has shown that humans have only limited information processing capabilities, and once these are exceeded, task performance decreases. Augmented Reality (AR) offers entire new possibilities to visualise information. Previous research on the relationship between the use of AR for information visualisation and the experienced cognitive load yielded contradictory results. By using the design science approach, we therefore aim to develop an AR decision support system. In a comparative eye-tracking study, we plan to examine how different types of AR information visualisation affect the experienced cognitive load of operations managers and thus decision-making. In this research-in-progress paper, we present the results of expert interviews with six operations managers who described three AR use cases in emergency management and five requirements for an AR decision support system

A Framework for Personalized Content Recommendations to Support Informal Learning in Massively Diverse Information WIKIS

Personalization has proved to achieve better learning outcomes by adapting to specific learners’ needs, interests, and/or preferences. Traditionally, most personalized learning software systems focused on formal learning. However, learning personalization is not only desirable for formal learning, it is also required for informal learning, which is self-directed, does not follow a specified curriculum, and does not lead to formal qualifications. Wikis among other informal learning platforms are found to attract an increasing attention for informal learning, especially Wikipedia. The nature of wikis enables learners to freely navigate the learning environment and independently construct knowledge without being forced to follow a predefined learning path in accordance with the constructivist learning theory. Nevertheless, navigation on information wikis suffer from several limitations. To support informal learning on Wikipedia and similar environments, it is important to provide easy and fast access to relevant content. Recommendation systems (RSs) have long been used to effectively provide useful recommendations in different technology enhanced learning (TEL) contexts. However, the massive diversity of unstructured content as well as user base on such information oriented websites poses major challenges when designing recommendation models for similar environments. In addition to these challenges, evaluation of TEL recommender systems for informal learning is rather a challenging activity due to the inherent difficulty in measuring the impact of recommendations on informal learning with the absence of formal assessment and commonly used learning analytics. In this research, a personalized content recommendation framework (PCRF) for information wikis as well as an evaluation framework that can be used to evaluate the impact of personalized content recommendations on informal learning from wikis are proposed. The presented recommendation framework models learners’ interests by continuously extrapolating topical navigation graphs from learners’ free navigation and applying graph structural analysis algorithms to extract interesting topics for individual users. Then, it integrates learners’ interest models with fuzzy thesauri for personalized content recommendations. Our evaluation approach encompasses two main activities. First, the impact of personalized recommendations on informal learning is evaluated by assessing conceptual knowledge in users’ feedback. Second, web analytics data is analyzed to get an insight into users’ progress and focus throughout the test session. Our evaluation revealed that PCRF generates highly relevant recommendations that are adaptive to changes in user’s interest using the HARD model with rank-based mean average precision (MAP@k) scores ranging between 100% and 86.4%. In addition, evaluation of informal learning revealed that users who used Wikipedia with personalized support could achieve higher scores on conceptual knowledge assessment with average score of 14.9 compared to 10.0 for the students who used the encyclopedia without any recommendations. The analysis of web analytics data show that users who used Wikipedia with personalized recommendations visited larger number of relevant pages compared to the control group, 644 vs 226 respectively. In addition, they were also able to make use of a larger number of concepts and were able to make comparisons and state relations between concepts

Improving Multi-Touch Interactions Using Hands as Landmarks

Efficient command selection is just as important for multi-touch devices as it is for traditional interfaces that follow the Windows-Icons-Menus-Pointers (WIMP) model, but rapid selection in touch interfaces can be difficult because these systems often lack the mechanisms that have been used for expert shortcuts in desktop systems (such as keyboards shortcuts). Although interaction techniques based on spatial memory can improve the situation by allowing fast revisitation from memory, the lack of landmarks often makes it hard to remember command locations in a large set. One potential landmark that could be used in touch interfaces, however, is people’s hands and fingers: these provide an external reference frame that is well known and always present when interacting with a touch display. To explore the use of hands as landmarks for improving command selection, we designed hand-centric techniques called HandMark menus. We implemented HandMark menus for two platforms – one version that allows bimanual operation for digital tables and another that uses single-handed serial operation for handheld tablets; in addition, we developed variants for both platforms that support different numbers of commands. We tested the new techniques against standard selection methods including tabbed menus and popup toolbars. The results of the studies show that HandMark menus perform well (in several cases significantly faster than standard methods), and that they support the development of spatial memory. Overall, this thesis demonstrates that people’s intimate knowledge of their hands can be the basis for fast interaction techniques that improve performance and usability of multi-touch systems