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Personal assistant agents capable of proactively offering assistance can be more helpful to their users through their ability to perform tasks that otherwise would require user involvement. This article characterizes the properties desired of proactive behavior by a personal assistant agent in the realm of task management and develops an operational framework to implement such capabilities. We present an extended agent architectural model that features a meta-level layer charged with identifying potentially helpful actions and determining when it is appropriate to perform them. The reasoning that answers these questions draws on a theory of proactivity that describes user desires and a model of helpfulness. Operationally, assistance patterns represent a compiled form of this knowledge, instantiating meta-reasoning over the agent's beliefs about its user's activities as well as over world state. The resulting generic framework for proactive goal generation and deliberation has been implemented as part of a personal assistant agent in the computer desktop domain.
Yorke‐Smith et al. (Fri,) studied this question.
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