Intelligent Agent Dialogue System for Implicit Goal Recognition
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Solution Overview
Problem
Existing intelligent agents are limited in their ability to handle complex user utterances that are not directly responsive to a previous dialogue message, understand implicit goals, recognize emotional sentiments, and provide effective responses in domains like finance where emotional customer utterances are common.
Innovation Solution
A computer-implemented method that involves a computing system receiving a dialogue message from a customer, parsing it to identify components and implied goals, generating a plan with action items based on the identified goals, and transmitting a verification message to the user for confirmation, while ensuring the plan complies with organizational policies and user sentiments are considered.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing intelligent agents are trained in a narrow domain for recognizing predefined commands, then they can handle expressly stated commands effectively, but they fail to understand implicit goals and complex user utterances
Solution Approach 1:
The intelligent agent is enhanced with multiple functional modules including sentiment analysis, implicit goal recognition, and context understanding capabilities. This allows the single system to perform both predefined command recognition and understand implicit user intentions, transforming it from a specialized tool into a multi-functional assistant that can handle diverse interaction types
2Adaptability or versatility
If intelligent agents handle complex user utterances with implicit goals, then they improve understanding capabilities, but they increase system complexity
Solution Approach 1:
The intelligent agent system is divided into distinct functional modules: sentiment analysis module, implicit goal recognition module, context understanding module, and response generation module. Each module handles a specific aspect of complex utterance processing, allowing the system to achieve high adaptability while maintaining manageable complexity through modular design
Solution Approach 2:
A dialogue context buffer serves as an intermediary structure that stores and manages conversation history, user preferences, and situational information. This mediator allows different modules to access and update shared context without direct complex interactions, simplifying the overall system architecture while enabling sophisticated implicit goal understanding
3Ease of operation
If intelligent agents provide empathetic responses to emotional customer utterances, then they improve customer service quality, but they require advanced sentiment analysis capabilities
Solution Approach 1:
The sentiment analysis module performs preliminary emotional state detection and classification before generating responses. By pre-processing and categorizing customer emotions (e.g., frustration, satisfaction, urgency), the system prepares appropriate empathetic response templates in advance, making the interaction smoother and reducing the computational difficulty of real-time sentiment analysis
Data Source
AI summary
System and method of generating an executable action item in response to natural language dialogue are disclosed herein. A computing system receives a dialogue message from a remote client device of a customer associated with an organization, the dialogue message comprising an utterance indicative of an implied goal. A natural language processor of the computing system parses the dialogue message to identify one or more components contained in the utterance. The planning module of the computing system identifies the implied goal. The computing system generates a plan within a defined solution space. The computing system generates a verification message to the user to confirm the plan. The computing system transmits the verification message to the remote client device of the customer. The computing system updates an event queue with instructions to execute the action item according to the generated plan upon receiving a confirmation message from the remote client device.