How might we craft simulations of human societies that reflect our lives? Many of the greatest challenges of our time, from encouraging healthy public discourse to designing pandemic responses, and building global cooperation for sustainability, must reckon with the complex nature of our world. The power to simulate hypothetical worlds in which we can ask "what if" counterfactual questions, and paint concrete pictures of how a multiverse of different possibilities might unfold, promises an opportunity to navigate this complexity. This course presents a tour of multiple decades of effort in social, behavioral, and computational sciences to simulate individuals and their societies, starting from foundational literature in agent-based modeling to generative agents that leverage the power of the most advanced generative AI to create high-fidelity simulations. Along the way, students will learn about the opportunities, challenges, and ethical considerations in the field of human behavioral simulations.
Note: Reading commentaries are due at 10:00 PM the day before the lecture on Canvas.
DATE | TOPIC | LECTURE AGENDA | ASSIGNMENTS |
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M, 9/23 (Week 1) |
A Tour of Simulations: Past, Present, and Future [Slides] |
What are simulations of human behavior? Where have we been, where are we now, and where are we headed? An introduction to the motivation and history behind simulations, from early methods like cellular automata and game theory, to agent-based modeling, and now modern generative AI-driven simulations. |
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W, 9/25 | Wicked Problems [Slides] |
What are the complex problems that simulations can help us tackle—problems that have been otherwise unsolvable or extremely challenging? An overview of the “wicked problems” faced by individuals and societies, and discussion of the grand challenges of our time and how simulations might offer new approaches. Required readings: |
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M, 9/30 (Week 2) |
Individuals, Groups, and Populations [Slides] |
When simulating human behavior, at what level of detail should we focus? Should we simulate the interactions of individuals and their groups, or predict the behaviors of entire populations? A look at the strengths and limitations of simulations at different levels of granularity. Required readings:
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W, 10/2 | Cognitive Architectures [Slides] |
How do we create a cognitive unit of the human mind? What were the foundational architectures that were envisioned, and how were they inspired by (and stylized differently from) human minds? What were their limitations? A history of cognitive architectures. Required readings: |
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M, 10/7 (Week 3) |
Architecting Generative Agents [Slides] |
How might we merge the vision of cognitive architectures with the advances in generative AI to build high-fidelity agents? What are the architectural similarities to past cognitive models, and what new opportunities do they bring? A review of generative agent architectures and the modern technologies that drive them. Required readings:
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[Assignment 1 Release] |
W, 10/9 | Interactive Worlds |
How should the generative agents we create interact with one another and with human users? What are the building blocks and environments in which these interactions should occur? A discussion of the environments and worlds where agents interact. Required readings:
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M, 10/14 (Week 4) |
Believability vs. Accuracy |
How do we know that our simulations are meaningful and representative of the world we live in? What are the axes for validating simulations, and what applications does each validation method empower? A discussion of methods for demonstrating simulation fidelity and their challenges. Required readings: |
[Project Proposal Release] |
W, 10/16 | Models of Individuals |
How might we create models of individuals that simulate how real people might behave and feel? How does this align with the original vision of bottom-up simulations, and what new advances enable this now? A discussion of generative agents that model individual behavior. Required readings:
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M, 10/21 (Week 5) |
Generative Agent-Based Models |
How can we combine generative agents of individuals to create a new generation of agent-based models capable of solving complex problems? What are the building blocks of these models, and what questions might they enable us to address? How does this approach differ from the previous generation of agent-based models? Required readings: |
[Due: Assignment 1] [Assignment 2 Release] |
W, 10/23 | AgentBank-CS222 |
How might we create a shared resource of models that emulate individuals to power generative agent-based models? What ethical considerations and boundaries ought we to consider, and can we draw inspiration from prior works? In this lecture, we will create a bank of agents that represent CS222. Required readings:
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M, 10/28 (Week 6) |
Equilibria and Butterflies |
Will generative agent-based models help us discover complex equilibria, or will they devolve into chaos? What new theories and scientific foundations do we need to interpret the equilibrium and chaos in worlds populated by generative agents? Required readings: |
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W, 10/30 | Language and Schema of Simulations |
How might we make simulations easy to create? What language and schema ought to describe the building blocks of our simulations, and where can we find inspiration for such a system? This discussion will explore prior systems that developed useful language and schema for complex systems (e.g., in data visualization, agent-based modeling). Required readings:
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[Due: Assignment 2] |
M, 11/4 (Week 7) |
Project Proposal: Day 1 |
Students will present and discuss their project proposals, outlining their goals, methodologies, and expected outcomes for their final project. |
[Presentation] |
W, 11/6 | Project Proposal: Day 2 |
Continuation of project proposal presentations and feedback. |
[Presentation] |
M, 11/11 (Week 8) |
Ethics and Limitations |
What ethical considerations and limitations must be addressed with the rise of powerful simulation technologies? How might simulations impact our ability to represent or reduce bias, protect privacy, and preserve human autonomy? Required readings:
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W, 11/13 | Guest Lecture 1: TBD |
Required readings:TBD |
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M, 11/18 (Week 9) |
Simulating Ourselves and Our Societies With AI |
Can simulations of human behavior be the killer application of modern AI? What are the potential implications, blue-sky use cases, and how might simulating ourselves and our societies shape the world we live in? Required readings: |
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W, 11/20 | Guest Lecture 2: TBD |
Required readings:TBD |
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M, 12/2 (Week 10) |
Project Presentation: Day 1 |
Students will present their final projects, discussing their simulation outcomes, challenges, and insights gained throughout the course. |
[Final Presentation] |
W, 12/4 | Project Presentation: Day 2 |
Continuation of the final project presentations and course wrap-up discussion. |
[Final Presentation] |