A user-guided cognitive agent for network service selection in pervasive computing environments

Connectivity is central to pervasive computing environments. We seek to catalyze a world of rich and diverse connectivity through technologies that drastically simplify the task of providing, choosing, and using wireless network services; creating a new and more competitive environment for these capabilities. A critical requirement is that users actually benefit from this rich environment, rather than simply being overloaded with choices. We address this with an intelligent software agent that transparently and continually chooses from among available network services based on its user´s individual needs and preferences, while requiring only minimal guidance and user interaction. We present an overview and model of the network service selection problem. We then describe an adaptive user agent that learns its user´s network service preferences from a very minimal, intuitive set of inputs, and autonomously and continually selects the service that best meets the user´s needs. Results from preliminary user experiments are presented that demonstrate the effectiveness of our agent.