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Coordination Patterns for Multi-Agent Systems
Created by Petter Smit
Design and reason about coordinated multi-agent systems using professional control-plane concepts: orchestration, protocols, shared state, hierarchy, incentives, and swarms. You’ll learn how to choose coordination topologies, specify message contracts, prevent systemic failure modes, and select the right coordination mechanism for your constraints.
Requirements
- LLM agent basics (tools, multi-step loops)
- Comfort with software control flow (graphs, branching, retries)
- Distributed-systems fundamentals (services, messaging, consistency)
- Basic optimization/incentives intuition (tradeoffs, payoffs)
What you'll learn
- Choose an appropriate coordination stance (centralized, decentralized, hybrid) based on system constraints and expected failure modes.
- Design an agentic workflow control plane using routing, parallel fan-out, convergence, and explicit stop conditions.
- Specify inter-agent communication contracts (schema, IDs, TTL, security/authorization) and explain how interoperability standards like A2A enable composition.
Learning path
7 modules • Each builds on the previous one
1
Multi-agent systems coordination fundamentals
Define multi-agent systems (MAS) and the core coordination problems: task/role allocation, shared state, conflict resolution, and convergence under partial observability. Build a vocabulary for when single-agent reasoning patterns fail at system scale.
2 videos9 min
2
Orchestration patterns for agentic workflows
Learn orchestration as the control-plane for agents: routing, task decomposition, delegation, tool scheduling, and retries. Contrast pipeline workflows, DAGs, event-driven flows, and supervisor-worker patterns for agent teams.
3 videos12 min
3
Inter-agent communication protocols and messaging
Study inter-agent communication as contracts: message types, schemas, conversation state, acknowledgements, and error semantics. Compare FIPA-ACL/KQML-style speech acts to modern RPC/pub-sub/event messaging patterns used in agent systems.
2 videos9 min
4
Coordination mechanisms: auctions, blackboards, voting
Learn canonical coordination mechanisms for MAS: contract net and auctions for task allocation, blackboard systems for shared context, and voting/consensus-style methods for decision aggregation. Focus on assumptions, guarantees, and failure modes.
1 video4 min
5
Hierarchical planning with manager-worker agents
Introduce hierarchical planning as a coordination strategy: role assignment, delegation, subgoal refinement, and escalation. Connect HTN-style ideas to practical supervisor-worker multi-agent designs and governance boundaries.
2 videos12 min
6
Cooperative games and incentive alignment
Use cooperative game theory to reason about collaboration: shared objectives, marginal contribution, coalition formation, and mechanism design. Translate incentives into coordination rules that reduce free-riding, reward hacking, and misaligned local optimizations.
2 videos10 min
7
Swarm intelligence for emergent coordination
Study decentralized coordination via swarm intelligence: local rules, stigmergy, and emergent global behavior (ant colony, particle swarm). Compare swarms to deliberative multi-agent coordination in terms of robustness, scalability, and controllability.
1 video6 min
Start Learning
Begin your learning journey
Modules7
Duration59 min
Science-backed learning
In-video quizzes and scaffolded content to maximize retention.
Key concepts
When And Why To Use Multi-Agent SystemsOrchestration Patterns (Graphs, Routing, Fan-Out/Fan-In)Inter-Agent Communication Contracts And Interoperability