AI Agent Interaction Controls for Intent-Based Function Selection
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Solution Overview
Problem
Users face difficulties in efficiently and accurately selecting the appropriate interaction function when interacting with multiple AI agents due to the complexity of available functions, leading to inefficiencies in user interaction processes.
Innovation Solution
An interaction method and device that utilize a machine learning model to determine and display relevant interaction functions based on user intent, allowing users to trigger specific functions directly through operation controls, thereby simplifying the interaction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users interact with multiple AI agents manually to find appropriate interaction functions, then users can access various functions, but interaction efficiency and accuracy deteriorate due to difficulty in finding required functions
Solution Approach 1:
The system performs preliminary action by automatically determining and recommending interaction functions before the user needs to search for them. The machine learning model analyzes user intent in advance and pre-identifies relevant functions, displaying them on the interaction interface so users can access needed functions without manual searching, thereby improving both efficiency and ease of operation
Solution Approach 2:
The system implements self-service by having the machine learning model automatically determine interaction functions based on user intent without requiring user guidance or manual selection. The system serves itself by autonomously identifying and presenting appropriate functions, reducing the cognitive load on users and improving interaction efficiency
2Measurement precision
If users manually search for interaction functions, then users can control the interaction process, but interaction accuracy deteriorates due to suboptimal function selection
Solution Approach 1:
The system applies feedback by continuously analyzing user intent through machine learning models and using this feedback to dynamically determine and recommend interaction functions. The model learns from user interactions and adjusts its function selection accordingly, improving accuracy over time while reducing the time users need to spend searching for appropriate functions
Data Source
AI summary
The present disclosure relates to an interaction method, device, electronic apparatus, storage medium and program product, and involves the technical field of artificial intelligence. The interaction method of the present disclosure comprises: displaying an interaction interface of a user and a first Agent; according to interaction information between the user and the first Agent, determining one or more interaction functions associated with the interaction information, wherein the one or more interaction functions are used to interact with the user based on an intention reflected in the interaction information; displaying operation controls of the one or more interaction functions; in response to the user's triggering of a target operation control in the operation controls of the one or more interaction functions, calling the interaction function corresponding to the target operation control to interact with the user.