Precomputation of context-sensitive policies for automated inquiry and action under uncertainty
First Claim
1. A method to facilitate mobile device operations, comprising:
- employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts;
utilizing each of a training input and a user input to develop logical rules or probabilistic user models in an offline computing environment, the probabilistic user models are associated with a model of interruptibilitv or a model of attendance;
generating a policy component that includes decision-making instructions derived from at least one of the logical rules or probabilistic user models developed in the offline computing environment; and
transmitting the policy component to a mobile device.
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Accused Products
Abstract
Learning, inference, and decision making with probabilistic user models, including considerations of preferences about outcomes under uncertainty, may be infeasible on portable devices. The subject invention provides systems and methods for pre-computing and storing policies based on offline preference assessment, learning, and reasoning about ideal actions and interactions, given a consideration of uncertainties, preferences, and/or future states of the world. Actions include ideal real-time inquiries about a state, using pre-computed value-of-information analyses. In one specific example, such pre-computation can be applied to automatically generate and distribute call-handling policies for cell phones. The methods can employ learning of Bayesian network user models for predicting whether users will attend meetings on their calendar and the cost of being interrupted by incoming calls should a meeting be attended.
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Citations
20 Claims
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1. A method to facilitate mobile device operations, comprising:
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employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts; utilizing each of a training input and a user input to develop logical rules or probabilistic user models in an offline computing environment, the probabilistic user models are associated with a model of interruptibilitv or a model of attendance; generating a policy component that includes decision-making instructions derived from at least one of the logical rules or probabilistic user models developed in the offline computing environment; and transmitting the policy component to a mobile device. - View Dependent Claims (2, 3, 4, 5)
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6. A computer implemented method for developing model policies system, comprising:
employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts; recording a set of appointment properties associated with a user'"'"'s electronic calendar; utilizing the set of appointment properties associated with the user'"'"'s electronic calendar to develop logical rules or probabilistic user models in an offline computing environment; developing a policy component that includes decision-making instructions that are derived from the logical rules or probabilistic user models; and encoding the policy component for implementation onto a mobile device. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A system to facilitate mobile device operations, comprising:
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a processor; a memory communicatively coupled to the processor and storing computer readable instructions for implementing the following components; a learning component for learning user models in an offline computing environment, the user models learned by utilizing each of a training input and a user input in the offline computing environment, the user models are associated with a model of interruptibility or a model of attendance; an encoding component for encoding an output from the user model according to one or more control policies; and a transmission component for transmitting the control policies to a remote device, the control policies executable in an online computing environment at the remote device apart from the offline computing environment.
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Specification