IP Library Granted Patent US 10,586,160
Granted Patent B2
US 10,586,160 · App. 16/382,367 · Granted Mar 10, 2020

Mood detection with intelligence agents

Inventors: Aaron K. Baughman (Silver Spring, MD); Diwesh Pandey (Bangalore, IN); John P. Perrino (Hedgesville, WV); Todd R. Whitman (Bethany, CT)
Assignee: International Business Machines Corporation
G06N5/043G06N3/006G06N5/022
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Quick Facts
Patent No.
US 10,586,160
App. No.
16/382,367
Granted
Mar 10, 2020
Kind
B2
Abstract

Embodiments of the present invention provide a computer system for increasing the quality of interactions between two or more entities. These entities are either individuals (e.g., human beings using a computer device) or artificial intelligence (AI) agents. The interactions between all of the entities within a computing environment are mapped and analyzed. Based on the mapped interactions, a relationship model is generated in order to run multiple applications within a computing environment.

Claims (15)

1. A computer system comprising:

one or more computer processors;

one or more computer readable storage media;

program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising:

program instructions to observe interactions between a plurality of individuals and a plurality of artificial intelligence (AI) agents;

program instructions to create a cognitive profile for each respective individual of the plurality of individuals and each respective AI agent of the plurality of AI agents using social media data, observation protocols, and biometric data for the plurality of individuals and special testing data for the plurality of AI agents, wherein the observation protocols comprise monitoring conversation tone and facial expressions during a respective interaction, and wherein the special testing data comprises sensor data, text data, and speech recognition data obtained during a respective interaction;

program instructions to map a set of interactions to each cognitive profile for each respective individual and AI agent based on the observed interactions between the plurality of individuals and the plurality of AI agents, wherein each respective individual and AI agent is represented as a data object and each interaction is represented as a data link;

program instructions to generate a plurality of relationship models based on the mapped set of interactions, wherein each relationship model is associated with a single interaction within the mapped set of interactions;

program instructions to complete a mood analysis for each respective interaction, wherein the mood analysis for each respective interaction comprise:

program instructions to identify a level of positive sentiment and a level of negative sentiment,

program instructions to identify a behavioral trigger that lead to a change in behavior by either the individual or the AI agent, and

program instructions to interpret facial expressions of either the individual or the AI agent;

program instructions to update the cognitive profile for each respective individual of the plurality of individuals and each respective AI agent of the plurality of AI agents based on the plurality of relationship models and the mood analysis;

program instructions to generate an action operation for each respective individual and AI agent based on the cognitive profile for the respective individual and respective AI agent to ameliorate respective interactions between the plurality of individuals and plurality of AI agents; and

program instructions to implement the action operation for each respective individual and AI agent.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 13, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: KYNDRYL, INC.
Reel/Frame 057885/0644 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 12, 2019
From: BAUGHMAN, AARON K.; PANDEY, DIWESH; PERRINO, JOHN P.; WHITMAN, TODD R.
To: INTERNATIONAL BUSINESS MACHINES COPORATION
Reel/Frame 048867/0844 →
Continuity (2)
Continuation 15604908 · May 25, 2017
Related Publication 20190236468A1 · Aug 1, 2019