Managing engagement methods of a digital assistant while communicating with a user of the digital assistant
A method for interacting by a digital assistant with a user of the digital assistant, comprising: determining by the digital assistant an action to be executed by the digital assistant, wherein the action is determined based on at least a sensed current state of the user and a sensed current state of an environment near the user; selecting an engagement method from a plurality of engagement methods based on the current state of the user, the current state of an environment near the user, and the selected action; generating a customized plan for executing the selected action based on at least the selected engagement method; and executing the generated plan by employing an input/output (I/O) device on which the digital assistant is executing.
1 . A method for interacting by a digital assistant with a user of the digital assistant, comprising:
determining by the digital assistant an action to be executed by the digital assistant, wherein the action is determined based on at least a sensed current state of the user and a sensed current state of an environment near the user;
selecting an engagement method from a plurality of engagement methods based on the current state of the user, the current state of an environment near the user, and the selected action, wherein each engagement method is a method for communicating with the user of the digital assistant that has a predefined interruption intensity with respect to the user;
generating a customized plan for executing the determined action based on at least the selected engagement method; and
executing the generated plan by employing an input/output (I/O) device on which the digital assistant is executing.
2 . The method of claim 1 , wherein determining the action further comprises:
collecting a dataset related to the user, the dataset including a least one piece of data sensed by at least one sensor coupled to the digital assistant; and
applying a machine learning model trained to determine a current state based on the collected dataset, wherein the current state is the state of the user and the state of the environment near the user in real-time or near real-time.
3 . The method of claim 2 , wherein collected dataset includes: real-time data related to a user obtained via the at least one sensor and historical data related to past activity of the user.
4 . The method of claim 3 , wherein at least one piece of historical data related to the user is obtained from at least one source external to the digital assistant.
5 . The method of claim 1 , wherein the selected engagement method is one of: intrusive proactive, direct proactive gateway, indirect proactive gateway, categorical proactive gateway, contextual proactive gateway, subtle proactive, and silent proactive.
6 . A system for interacting by a digital assistant with a user of the digital assistant the system, comprising:
a processing circuitry; and
a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
determine an action to be executed by the digital assistant, wherein the action is determined based on at least a sensed current state of the user and a sensed current state of an environment near the user;
select an engagement method from a plurality of engagement methods based on the current state of the user, the current state of an environment near the user, and the selected action, wherein each engagement method is a method for communicating with the user of the digital assistant that has a predefined interruption intensity with respect to the user;
generate a customized plan for executing the determined action based on at least the selected engagement method; and
execute the generated plan by employing an input/output (I/O) device on which the digital assistant is executing.
7 . The system of claim 6 , wherein to determine the action further comprises:
collect a dataset related to the user, wherein the dataset includes a least one piece of data sensed by at least one sensor coupled to the digital assistant; and
apply a machine learning model trained to determine a current state based on the collected dataset, wherein the current state is the state of the user and the state of the environment near the user in real-time or near real-time.
8 . The system of claim 7 , wherein collected dataset includes: real-time data related to a user obtained via the at least one sensor and historical data related to past activity of the user.
9 . The system of claim 8 , wherein at least one piece of historical data related to the user is obtained from at least one source external to the digital assistant.
10 . The system of claim 6 , wherein the selected engagement method is one of: intrusive proactive, direct proactive gateway, indirect proactive gateway, categorical proactive gateway, contextual proactive gateway, subtle proactive, and silent proactive.
11 . A method performed by an input/output (I/O) device having a digital assistant, at least one sensor, and at least one resource, the method comprising:
determining by the digital assistant an action to be executed by the I/O device, wherein the action is determined based on at least a sensed current state of a user of the I/O device and a current state of an environment near the user, wherein the at least one sensor is used to sense information upon which is based at least one of the current state of the user and the current state of the environment near the user;
selecting an engagement method from a plurality of engagement methods based on the current state of the user, the current state of an environment near the user, and the determined action, wherein each engagement method is a method for communicating with the user of the digital assistant that has a predefined interruption intensity with respect to the user;
generating a customized plan for executing the determined action based on at least the selected engagement method; and
executing the generated plan by at least operation of at least one of the at least one resource.
12 . The method of claim 11 , wherein determining the action further comprises:
collecting a dataset related to the user, the dataset including a least one piece of data sensed by at least one sensor coupled to the digital assistant; and
applying a machine learning model trained to determine a current state based on the collected dataset, wherein the current state is the state of the user and the state of the environment near the user in real-time or near real-time.
13 . The method of claim 12 , wherein collected dataset includes: real-time data related to a user obtained via the at least one sensor and historical data related to past activity of the user.
14 . The method of claim 13 , wherein at least one piece of historical data related to the user is obtained from at least one source external to the digital assistant.
15 . The method of claim 11 , wherein the selected engagement method is one of: intrusive proactive, direct proactive gateway, indirect proactive gateway, categorical proactive gateway, contextual proactive gateway, subtle proactive, and silent proactive.
16 . The method of claim 11 , wherein the at least one sensor is a virtual sensor.
17 . The method of claim 11 , wherein the at least one sensor is part of the at least one resource.