Capture Agent for Autonomous Session Replay
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Solution Overview
Problem
Previous cognitive computing systems lack a method for capturing and replaying previous sessions in a context that is usable and useful for users, making it difficult for users to re-present or replay sequences of requests and responses from previous interactions with autonomous agents.
Innovation Solution
The system includes a capture agent that subscribes to other agents, stores messages in a memory, and registers new subscriptions, allowing for the replay of messages based on specific criteria, enabling users to interact with autonomous agents and collaborate across time and environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a capture agent subscribes to all agents and stores all messages, then complete session capture is achieved, but system complexity and storage requirements increase
Solution Approach 1:
The capture agent proactively subscribes to agents and registers for new subscriptions before sessions occur, ensuring complete capture capability is established in advance. This preliminary setup allows the system to capture all session information without missing any interactions.
Solution Approach 2:
The capture agent acts as an intermediary component that sits between agents and the storage system. It receives messages from agents, stores them in the message store, and manages subscription registrations, thereby simplifying the overall system architecture while ensuring complete information capture.
2Reliability
If the capture agent registers for all new subscriptions dynamically, then complete message capture is ensured, but processing overhead and system load increase
Solution Approach 1:
The capture agent implements a feedback mechanism by registering for new subscription notifications. When agents create new subscriptions, the capture agent receives notifications and automatically registers for those subscriptions, ensuring continuous and reliable message capture without manual intervention.
Solution Approach 2:
The capture agent autonomously manages its own subscription registrations. It automatically detects new subscriptions through notifications and registers itself without requiring external management, reducing system overhead while maintaining complete capture reliability.
3Measurement precision
If messages are stored with full contextual indicators, then replay accuracy is improved, but storage requirements and data volume increase
Solution Approach 1:
The message storage system segments contextual information into essential and optional components. Only essential contextual indicators necessary for accurate replay are stored with each message, while optional detailed context can be retrieved separately if needed, reducing overall storage requirements while maintaining replay accuracy.
Data Source
AI summary
According to an embodiment of the present invention, a method for operating a cognitive computing system comprises starting a capture agent on a processor, subscribing the capture agent to a second agent, receiving a first message from the second agent, storing the received first message in a memory, receiving a notification of a new subscription from a third agent, and registering the capture agent to subscribe to the new subscription from the third agent.