AIAdvanced#Collaboration#Architecture
Multi-Agent System (MAS)
M
Definition
A framework where multiple AI agents work together to solve a task, such as one agent managing risk while another finds entries.
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Concept Diagram
Key Takeaways
1
MAS deploys multiple specialized AI agents that collaborate to solve complex trading problems
2
Each agent has a narrow specialization like sentiment analysis, technical analysis, or execution
3
Agents communicate through shared protocols and can negotiate, compete, or cooperate
4
Reduces single-point-of-failure risk compared to relying on a single monolithic AI model
Practical Example
Agent Alpha analyzes whale wallets, Agent Beta monitors Twitter sentiment, Agent Gamma tracks funding rates — they vote on a consensus signal before Agent Delta executes the trade, creating a robust multi-layer decision system.
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Related Terms
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AgenticityThe degree to which an autonomous entity can perceive its environment, make decisions, and execute actions independently via smart contracts or LLMs.
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VIRTUAL EcosystemA launchpad and liquidity layer specifically for autonomous AI agents on Base and Solana chains.
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Agentic MeshA decentralized network where different specialized agents communicate and swap services (e.g., a news-agent selling data to a trade-agent).
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Sentiment EngineA specialized sub-system that parses thousands of tweets/news per second to gauge if the market is fearful, euphoric, or neutral.
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