Phase 2: Coordination & Agreement · ~75 minutes · Python (stdlib)

Voting, Self-Consistency, and Debate Topology

The cheapest aggregation: sample N independent agents, majority-vote.

Hiring signal: Can operate voting, self-consistency, and debate topology in production

Introduction

Wang et al. 2022 self-consistency did this with one model sampled N times. Multi-agent extends it with heterogeneous agents to escape monoculture — different models, different prompts, different temperatures, different contexts. Beyond majority vote, debate topology matters: MultiAgentBench (arXiv:2503.01935, ACL 2025) evaluated star / chain / tree / graph coordination and found graph best for research, with a "coordination tax" past ~4 agents. AgentVerse (ICLR 2024) documents two emergent patterns — volunteer behaviors and conformity behaviors — and conformity is both a feature (finding consensus) and a risk (groupthink, Lesson 24). This lesson maps the topology space, builds each variant, and measures the coordination tax.

Type: Learn + Build Languages: Python (stdlib) Prerequisites: Phase 16 · 07 (Society of Mind and Debate), Phase 16 · 14 (Consensus and BFT) Time: ~75 minutes

Objective

Learning objectives

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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