References: Multi-Agent Workflows, Debate, and Consensus

1. Multi-agent system - Wikipedia - Offers an accessible overview of Multi-agent system, including definitions, methods, examples, limitations, and related concepts. This foundation helps students reason carefully about orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

2. Consensus decision-making - Wikipedia - Offers an accessible overview of Consensus decision-making, including definitions, methods, examples, limitations, and related concepts. Its examples help students evaluate evidence for orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

3. Debate - Wikipedia - Offers an accessible overview of Debate, including definitions, methods, examples, limitations, and related concepts. It supplies useful context for decisions about orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

4. An Introduction to MultiAgent Systems (2nd ed.) - Michael Wooldridge - Wiley - Explains agent interaction, coordination, cooperation, negotiation, communication, and collective decision-making through models and examples. Its sustained treatment supports work on orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

5. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations - Yoav Shoham and Kevin Leyton-Brown - Cambridge University Press - Provides rigorous foundations for distributed decision-making, incentives, communication, voting, cooperation, and strategic interaction among agents. Its cases illuminate tradeoffs involved in orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

6. AI Agent Orchestration Patterns - Microsoft Learn - Compares sequential, concurrent, group-chat, handoff, and magentic orchestration patterns, including their coordination costs, failure modes, and suitable use cases. Its methods give teams a starting point for orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

7. Building Effective Agents - Anthropic - Distinguishes workflows from agents and illustrates routing, parallelization, orchestration, evaluation, tool design, and appropriate control of system complexity. Its comparisons clarify choices involved in orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

8. Agents - OpenAI - Explains how models, tools, knowledge, instructions, guardrails, and orchestration combine into bounded agent workflows that can be tested and monitored. Its framework strengthens responsible work on orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

9. Demystifying Evals for AI Agents - Anthropic - Explains agent evaluation design, realistic tasks, outcome and process graders, repeated trials, transcript review, and analysis of variable behavior. Its examples show how evidence informs orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.

10. Working with Evals - OpenAI - Introduces test data, evaluation criteria, graders, repeated runs, and comparison workflows for measuring model behavior instead of relying on impressions. Its implementation advice helps teams practice orchestrating independent agents, controlled context, handoffs, debate, consensus, and disagreement.