Learning User Preferences for Wireless Services Provisioning
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Connectivity is central to pervasive computing environments.We seek to catalyze a world of rich and diverse connectivitythrough technologies that drastically simplify thetask of providing, choosing, and using wireless network services;creating a new and more competitive environment forthese capabilities.A critical requirement is that users actually benefit fromthis rich environment, rather than simply being overloadedwith choices. We address this with an intelligent softwareagent that transparently and continually chooses fromamong available network services based on its user's individualneeds and preferences, while requiring only minimalguidance and user interaction. In this paper, we present anoverview and model of the network service selection problem.We then describe an adaptive user agent that learnsits user's network service preferences from a very minimal,intuitive set of inputs, and autonomously and continuallyselects the service that best meets the user's needs. Resultsfrom preliminary user experiments are presented thatdemonstrate the effectiveness of our agent.