Affiliations: Adaptive Risk Management Lab, Faculty of Computer Science, The University of New Brunswick, Fredericton, NB, Canada
Correspondence:
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Corresponding author: Alexis Morris, Adaptive Risk Management Lab, Faculty of Computer Science, The University of New Brunswick, Fredericton, NB, Canada. E-mail: [email protected]
Abstract: Brain-monitoring is quickly becoming an important field of research, with potentially significant impacts on how people will interact with technology. As understandings of the inner-workings of the brain become more accurate technologies are becoming more advanced, smaller, cheaper, and ubiquitous. It is expected that new forms of computing that take advantage of brain states will be developed. This will enable systems to be highly aware of user mental contexts (emotions, intentions, and moods). These systems would display higher autonomic behavior and would streamline user-interaction while managing the use of brain context data for applications and services. There are few studies of how to develop and make use of agent architectures in this new domain. Current approaches target a single user and application situation. To be ubiquitous it is unrealistic for applications to have specialized overhead for individual users. Personalizable, but distributed approaches are needed. To realize a general purpose agent for brain-monitoring and management of brain context is the goal of this work. This involves the selection of a brain-monitoring paradigm, the selection of an agent architecture paradigm, an inferencing mechanism, and the combination of the three towards a unified framework. Core motivations are discussed, and an early agent framework design (FRIEND) is presented, along with proposed proof-of-concept applications for using brain context.
Keywords: Ambient intelligence, cognitive inference, context awareness, multi-agent systems
