Methods and systems for deploying and managing scalable multi-service virtual assistant platform

• US 10,629,191 B1
• Filed: 08/01/2019
• Issued: 04/21/2020
• Est. Priority Date: 06/16/2019
• Status: Active Grant

• Current Assignee: Rs1needle, Inc.
• Original Assignee: Linc Global, Inc.
• Inventors: Cheng, Fang, Wu, Dennis, Chen, Jian Da
• Primary Examiner(s): Roberts, Shaun
• Application Number:
  US16/528,926
• Time in Patent Office: 264 Days
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 16/90332 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation
• CPC Class Codes: G06F 40/56 Natural language generation
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G10L 15/18 using natural language modelling
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: H04L 51/02 using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
• CPC Class Codes: H04L 51/214 using selective forwarding

Abstract

The present invention is a scalable multi-service virtual assistant platform that can construct a fluid and dynamic dialogue by assembling responses to end user utterances from two kinds of agents, information agents and action agents. The information agents and action agents are managed by a masterbot or arbiter. The virtual assistant can gain new skills by getting instructions about a new service expressed in a form of pre-requisites and action combinations; the virtual assistant platform automatically handles dialogue generation, arbitration and optimization to survey prerequisites from the end user, and eventually to take action. The present invention allows a large number of services to implemented using a small number of building blocks. These building blocks can be used to assemble a much larger number of services. In turn, each service can be delivered through a large variety of conversations with end users, enabling a fluid and dynamic dialogue to be seamlessly implemented.

Claims

1. A system for a virtual assistant platform, comprising:

at least one memory device that stores computer-executable instructions; and

at least one processor configured to access the memory device, wherein the processor is configured to execute the computer-executable instructions to;

receive one or more utterances from a user;

generate a parsed user input from the one or more utterances using a natural language understanding (NLU) module;

obtain at least one information value from the parsed user input and/or contextual data using a plurality of information agents;

perform one or more actions in response to the parsed user input, the contextual data, and/or the at least one information value using a plurality of action agents, wherein the plurality of information agents and the plurality of action agents are interrelated via one or more relationship connections, wherein the one or more relationship connections comprises at least a prerequisite connection that activates one or more prerequisite information agents to fulfill one or more prerequisite conditions for a given action agent; and

arbitrate an activation of the plurality of information agents and the plurality of action agents using a masterbot to render a response back to the user.

2. The system of claim 1, wherein at least one of the plurality of information agents is adapted to understand the parsed user input from the user to extract the information value directly from the parsed user input.

3. The system of claim 1, wherein at least one of the plurality of information agents is adapted to infer the information value from the parsed user input, wherein the inferring is activated in response to determining that a given information agent cannot obtain the information value by understanding the parsed user input directly.

4. The system of claim 3, wherein at least one of the plurality of information agents is adapted to infer the information value by accessing one or more contextual data sources for the contextual data and is adapted to infer the information value from the parsed user input and the contextual data.

5. The system of claim 4, wherein at least one of the plurality of information agents is adapted to query the user for the information value by generating a natural language query using a natural language generation (NLG) module, wherein the querying is activated in response to determining that the information agent cannot obtain the information value by understanding the parsed user input or inferring the information value.

6. The system of claim 1, wherein at least one of the plurality of information agents is adapted to obtain the information value by activating one or more other information agents, wherein the one or more other information agents are activated in response to determining that the at least one information agent cannot obtain the information value by understanding the parsed user input or inferring the information value.

7. The system of claim 1, wherein at least one of the plurality of action agents performs the one or more actions by triggering one or more internal services to perform one or more services.

8. The system of claim 7, wherein at least one of the plurality of action agents performs the one or more actions by accessing one or more Application Programming Interface (API) gateways to external services to perform the one or more services.

9. The system of claim 1, wherein the masterbot is adapted to activate one or more of the information agents in order to meet one or more prerequisite connections for a given action agent, wherein the given action agent utilizes the one or more activated information agents to obtain one or more information values needed to perform the one or more actions.

10. The system of claim 1, wherein at least one of the plurality of action agents is adapted to generate a natural language reply to the user using a natural language generation (NLG) module.

11. The system of claim 1, wherein at least one of the plurality of action agents is adapted to change a system state by setting up a follow-up action agent.

12. The system of claim 1, wherein the masterbot evaluates a performance of the plurality of information agents and the plurality of action agents using machine learning to adjust the activation of the information agents and the action agents.

13. The system of claim 1, wherein the masterbot generates the response to the user using a natural language generation (NLG) module from information supplied by the information agents and/or the action agents.

14. The system of claim 1, wherein the one or more relationship connections are further selected from the group consisting of a set-value connection between an action agent and an information agent, a follow-up connection between two action agents, and an inference connection between two information agents.

15. The system of claim 14, wherein the set-value connection interrelates the plurality of information agents and the plurality of action agents via a plurality of set-value actions, wherein a given set-value action for a given action agent is used to set an information value for one or more corresponding information agents which are later used by the corresponding information agents.

16. The system of claim 14, wherein the follow-up connection interrelates the plurality of action agents amongst themselves which determine when a given action agent follows-up after another given action agent terminates.

17. The system of claim 14, wherein the inference connection interrelates the plurality of information agents amongst themselves which determine when a given information agent activates one or more related information agents in order to fulfill one or more information values of the given information agent which are later used by the given information agent.

18. A non-transitory, computer-readable medium storing computer-executable instructions for a multi-service virtual assistant platform which, when executed by a processor, cause the processor to perform operations comprising steps to:

receive one or more utterances from a user;

generate a parsed user input from the one or more utterances using a natural language understanding (NLU) module;

obtain at least one information value from the parsed user input and/or contextual data using a plurality of information agents;

perform one or more actions in response to the parsed user input, the contextual data, and/or the at least one information value using a plurality of action agents, wherein the plurality of information agents and the plurality of action agents are interrelated via one or more relationship connections, wherein the one or more relationship connections comprises at least a prerequisite connection that activates one or more prerequisite information agents to fulfill one or more prerequisite conditions for a given action agent; and

arbitrate an activation of the plurality of information agents and the plurality of action agents using a masterbot to render a response back to the user.

19. A computer-implemented method for a multi-service virtual assistant platform which, when executed by a processor, causes the processor to perform steps comprising:

receiving one or more utterances from a user;

generating a parsed user input from the one or more utterances using a natural language understanding (NLU) module;

obtaining at least one information value from the parsed user input and/or contextual data using a plurality of information agents;

performing one or more actions in response to the parsed user input, the contextual data, and/or the at least one information value using a plurality of action agents, wherein the plurality of information agents and the plurality of action agents are interrelated via one or more relationship connections, wherein the one or more relationship connections comprises at least a prerequisite connection that activates one or more prerequisite information agents to fulfill one or more prerequisite conditions for a given action agent; and

activating one or more of the plurality of information agents and the plurality of action agents using a masterbot to render a response back to the user.