🤝 Multi-Agent Systems
Build collaborative AI systems with coordinated autonomous agents
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0 / 5 completedIntroduction to Multi-Agent Systems
🎯 What are Multi-Agent Systems?
Multi-agent systems (MAS) are computational systems where multiple autonomous agents interact to solve problems beyond individual capabilities. Each agent has specific roles, goals, and capabilities, working together through coordination and communication protocols.
The whole is greater than the sum of parts. Agents collaborate, delegate, and combine strengths to achieve complex goals through emergent behavior.
Customer service, sales, operations working together autonomously
Drone swarms, warehouse robots, smart home device coordination
NPC teams, traffic simulation, economic modeling
🔑 Core Characteristics
Autonomy
Agents operate independently, making decisions without constant human oversight
Communication
Agents exchange information through messages and shared memory
Specialization
Each agent has unique capabilities and domain expertise
Coordination
Agents synchronize actions to avoid conflicts and optimize outcomes
✅ Benefits
- •Scalable parallel processing
- •Fault tolerance and redundancy
- •Specialized expertise combination
- •Complex problem decomposition
⚠️ Challenges
- •Coordination overhead
- •Communication bottlenecks
- •Conflict resolution complexity
- •Emergent behavior unpredictability