Multi-Agent Request Processing Through Dynamic Agent Selection
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Solution Overview
Problem
Existing multi-agent collaboration methodologies struggle to effectively process user requests requiring capabilities beyond the scope of individual agent modules, leading to limitations in generating comprehensive processing results, especially when agents are specialized for specific domains.
Innovation Solution
A system and method for multi-agent collaboration that allows agents to determine and request assistance from other agents through natural language-based peer-to-peer communication, enabling the selection of optimal agents to process tasks beyond their capabilities, using detailed information on agent domains, roles, and skills, and leveraging large language models for task configuration and execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple expert agents are implemented to handle specialized tasks, then the processing capability for specific domains is improved, but the complexity of the system increases
Solution Approach 1:
The system divides the processing capability into multiple independent expert agents, each specialized in specific domains. This segmentation allows the system to handle complex tasks by coordinating specialized agents rather than requiring a single monolithic system to handle all possibilities, thus improving adaptability while managing complexity through modular architecture.
Solution Approach 2:
The host agent serves as a universal coordinator that can invoke any expert agent regardless of domain specialization. This multi-functionality at the host level allows the system to maintain high versatility for handling diverse tasks while keeping individual agent components relatively simple and focused on their specific expertise.
2Ease of operation
If pre-determined collaboration operations are used for multi-agent collaboration, then the collaboration process is simplified, but the adaptability to handle requests beyond individual agent capabilities is reduced
Solution Approach 1:
The collaboration process is made dynamic through the host agent's ability to invoke expert agents based on real-time analysis of user requests and agent capabilities. Rather than following fixed pre-determined collaboration workflows, the system adapts its collaboration structure on-the-fly, allowing flexible composition of agents needed for each specific request while maintaining operational simplicity through automated decision-making.
Solution Approach 2:
The host agent autonomously determines which expert agents to invoke based on the user request and available agent capabilities, without requiring manual configuration or pre-determined collaboration protocols. This self-service approach simplifies operation by automating the collaboration decision-making process while maintaining high adaptability to diverse task requirements.
Data Source
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AI summary
Provided is a computing system for processing a user's request based on multi-agent collaboration. The computing system comprises an agent information storage device storing detailed information on each of a plurality of agents, the detailed information including information on a responsible field of each agent and an agent execution system executing a first agent responsible for processing a user request introduced through a first channel and a second agent responsible for processing a user request introduced through a second channel different from the first channel.