The objective of this project is to solve technical problems that need to be overcome to build socio-cognitive orthotic systems, which will augment human cognitive capabilities to promote social interactions. Information technology can help a person with cognitive impairment in managing his or her everyday life, by modeling the activities the person wants or needs to do, monitoring the person's activities as they unfold, and guiding the person to ensure that the most important activities occur. Thus, information technology can provide a cognitive orthotic that augments reduced cognitive abilities and helps the person live independently. Unfortunately, though, replacing dependence on other people with reliance on information technology can mean fewer opportunities for social interaction, which in turn can lead to loneliness and isolation.
To solve this problem, a person's socio-cognitive orthotic system could be networked with the systems of other people. Now, as time passes and people make choices about their activities, these choices can help bring about, or make more difficult, potential planned social activities. Thus, the networked orthotic systems, as agents acting on behalf of their associated users, need to behave as a collaborative multi-agent system to cooperatively manage the users' plans. Each separate system needs to monitor and guide its user's activities while giving its user as much autonomy as possible to independently control his or her day, and yet must also attempt to maintain desirable options for social activities that obviously must be timed well with the schedules of other participants. And all this should be done in a timely, adaptive, and efficient way.
The hypothesis that this project will investigate is that incorporating hierarchical activity abstractions and richer constraint models into well-founded temporal constraint network representations, and augmenting distributed constraint reasoning techniques to adaptively handle these more flexible representations, will provide a principled and efficient foundation for collaborative plan management systems for individual and social activities. Some of the key ideas to be investigated include: using abstract activity specifications that can postpone commitments about which particular activities will be done, when, and by whom, until decisions need to be made; developing algorithms that can exploit, and even introduce, abstractions in activities, their timing, and (for social activities) their participants to increase flexibility and to reduce computation and communication; representing alternative activity plans, even if they contradict each other, to leave many options open for important social (and individual) activities; and capturing activity importance and costs of violating constraints in the models to calculate tradeoffs in the (likely) case where the multi-agent plans evolve such that contentions arise.
The project will build from the current state-of-the-art in hierarchical multi-agent planning and coordination, single-agent plan management, and distributed constraint reasoning. It will incorporate new ideas in multi-agent activity modeling, continual distributed constraint network maintenance, and adaptive refinement and constraint relaxation mechanisms, to innovate practical computational techniques that will scale to multi-agent applications involving complex interrelationships in continually-evolving worlds. The project will design, develop, analyze, and empirically test novel techniques for continual collaborative multi-agent management of loosely-coupled plans, a problem that deserves more study and for which no general intuitions or solution methods exist.
Developing socio-cognitive orthotics, where information technology can be cost-effectively used to simultaneously promote independence while combating isolation for cognitively-impaired people, can have tremendous societal benefits. A further expected impact of this project is that it will form the basis for a course in information technology for cognitive assistance, which will introduce first-year undergraduates not only to computer science concepts but also to the possible societal contributions computer scientists can make. It is expected that such a course can attract more students, and particularly women and minorities, to major in computer science.
