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AI From Scratch/Phase 16/Lesson 01/~60 minutes

Why Multi-Agent?

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One agent hits a wall. The smart move is not a bigger agent - it is more agents.

Back to phaseMulti-Agent & Swarms Next lessonHeritage of FIPA-ACL and Speech Acts

Phase 16

Multi-Agent & Swarms

01Why Multi-Agent?02Heritage of FIPA-ACL and Speech Acts 03Communication Protocols 04The Multi-Agent Primitive Model 05Supervisor / Orchestrator-Worker Pattern 06Hierarchical Architecture and Its Failure Mode 07Society of Mind and Multi-Agent Debate 08Role Specialization — Planner, Critic, Executor, Verifier 09Parallel / Swarm / Networked Architectures 10Group Chat and Speaker Selection 11Handoffs and Routines — Stateless Orchestration 12A2A — The Agent-to-Agent Protocol 13Shared Memory and Blackboard Patterns 14Consensus and Byzantine Fault Tolerance for Agents 15Voting, Self-Consistency, and Debate Topology 16Negotiation and Bargaining 17Generative Agents and Emergent Simulation 18Theory of Mind and Emergent Coordination 19Swarm Optimization for LLMs (PSO, ACO)20MARL — MADDPG, QMIX, MAPPO 21Agent Economies, Token Incentives, Reputation 22Production Scaling — Queues, Checkpoints, Durability 23Failure Modes — MAST, Groupthink, Monoculture, Cascading Errors 24Evaluation and Coordination Benchmarks 25Case Studies and the 2026 State of the Art

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Phase 16

Multi-Agent & Swarms

01Why Multi-Agent?02Heritage of FIPA-ACL and Speech Acts 03Communication Protocols 04The Multi-Agent Primitive Model 05Supervisor / Orchestrator-Worker Pattern 06Hierarchical Architecture and Its Failure Mode 07Society of Mind and Multi-Agent Debate 08Role Specialization — Planner, Critic, Executor, Verifier 09Parallel / Swarm / Networked Architectures 10Group Chat and Speaker Selection 11Handoffs and Routines — Stateless Orchestration 12A2A — The Agent-to-Agent Protocol 13Shared Memory and Blackboard Patterns 14Consensus and Byzantine Fault Tolerance for Agents 15Voting, Self-Consistency, and Debate Topology 16Negotiation and Bargaining 17Generative Agents and Emergent Simulation 18Theory of Mind and Emergent Coordination 19Swarm Optimization for LLMs (PSO, ACO)20MARL — MADDPG, QMIX, MAPPO 21Agent Economies, Token Incentives, Reputation 22Production Scaling — Queues, Checkpoints, Durability 23Failure Modes — MAST, Groupthink, Monoculture, Cascading Errors 24Evaluation and Coordination Benchmarks 25Case Studies and the 2026 State of the Art

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The Landscape of Emerging AI Agent ArchitecturesReading AutoGen: Enabling Next-Gen LLM ApplicationsReading Claude Code subagents documentationReading CrewAI documentationReading Multi Agent DecisionPrompt single_vs_multi.tsCode