Evaluation and Visualization Tools for Crowdsourcing Games
This project investigates the use of game analytics to evaluate games designed for citizen science and understand problem solving strategies in crowd sourced games.
This project will create a new category of intelligent, autonomous virtual or robotic agent, which is continuously operating and interacting with humans – always on – for long periods of time and whose primary motivation is building and maintaining long-term social relationships with humans. The initial application focus of this research is to provide companionship and social support and to promote wellness for older adults who are living alone.
This project will create a new category of intelligent, autonomous virtual or robotic agent, which is continuously operating and interacting with humans – always on – for long periods of time and whose primary motivation is building and maintaining long-term social relationships with humans. The initial application focus of this research is to provide companionship and social support and to promote wellness for older adults who are living alone. For example, during a typical day, an always-on relational agent might play a social game of cards with the adult, act as an exercise coach and help arrange visits or phone calls with the adult’s family and friends.
A new integrated theory of social agency, called SharedPlans Relationship Theory, will be developed to serve as a principled foundation for these relational agents. The theory will be grounded in an always-on relational software architecture, which will be distributed as open-source for others to use and extend. Using a participatory design process, including home and laboratory studies, the target user population will help develop the specifications for a relational agent, which will then be constructed using the theory and software architecture, and placed in users’ homes for long-term (month or more) longitudinal evaluation.
This project will make fundamental, theoretical contributions to models of relationship, sociality, interactional engagement and social support. The effort will also produce new insights into how people in general, and older adults in particular, enact social support at the relational, activity and micro-behavioral levels of analysis. The new always-on relational software architecture will be a fundamental advance over current agent architectures, which only support brief, focused interactions around a well-specified task. This architecture will also support incremental extension of agent capabilities and be able to control either virtual and robotic agent embodiments.
Social isolation is a broadly troubling trend in modern society. Always-on relational agents have the potential to counteract this isolation both directly, by providing companionship, and as intermediaries, by putting isolated people in contact with other people, both electronically and physically. Companionship and social support are also known to be significant positive factors in disease recovery and mortality, especially for older adults. The application focus of this project therefore has the potential for helping with health care cost control.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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Timothy Bickmore. “Social support agents for older adults: longitudinal affective
computing in the home,” Journal on Multimodal User Interfaces, v.9, 2014, p. 79.
BOOKS/ONE TIME PROCEEDING
Ring, L., Bickmore, T., & Schulman, D.. “Longitudinal Affective Computing: Virtual Agents that Respond to User Mood”, 09/01/2011-08/31/2012, 2012, “Intelligent Virtual Agents conference (IVA)”.
Vardoulakis, L., Ring, L., Barry, B., Sidner, C., & Bickmore, T. “Designing Relational Agents as Long Term Social Companions for Older Adults”, 09/01/2011-08/31/2012, 2012, “Intelligent Virtual Agents conference (IVA)”.
The objective of this research is to develop a comprehensive theoretical and experimental cyber-physical framework to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics.
Specifically, the approach is applied to examine individualized remote rehabilitation with an intelligent, articulated, and adjustable lower limb orthotic brace to manage Knee Osteoarthritis, where a visual-sensing/dynamical-systems perspective is adopted to: (1) track and record patient/device interactions with internet-enabled commercial-off-the-shelf computer-vision-devices; (2) abstract the interactions into parametric and composable low-dimensional manifold representations; (3) link to quantitative biomechanical assessment of the individual patients; (4) facilitate development of individualized user models and exercise regimen; and (5) aid the progressive parametric refinement of exercises and adjustment of bracing devices. This research and its results will enable us to understand underlying human neuro-musculo-skeletal and locomotion principles by merging notions of quantitative data acquisition, and lower-order modeling coupled with individualized feedback. Beyond efficient representation, the quantitative visual models offer the potential to capture fundamental underlying physical, physiological, and behavioral mechanisms grounded on biomechanical assessments, and thereby afford insights into the generative hypotheses of human actions.
Knee osteoarthritis is an important public health issue, because of high costs associated with treatments. The ability to leverage a quantitative paradigm, both in terms of diagnosis and prescription, to improve mobility and reduce pain in patients would be a significant benefit. Moreover, the home-based rehabilitation setting offers not only immense flexibility, but also access to a significantly greater portion of the patient population. The project is also integrated with extensive educational and outreach activities to serve a variety of communities.