Designing Consensus: Gamified Modeling and Simulation of Collaborative Decision-Making

Lecture Resources

Jan 16 - Design as a Game

Overview and introduction of core concepts. Introduce classical physical board games and their mechanisms, including Monopoly, Tiny Towns, and Small City.

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Jan 21 - Modeling and Collaborative Decision-Making

Further introduction to game theory and decision-making from a computational perspective. Explore how we can turn a game (like Go) into a format the computer can recognize, play, and learn with. A touch on PettingZoo as a standard for creating digital environments. A brief introduction to traditional decision-making modeling approaches, such as behavioral trees, finite state machines, and rule-based systems.

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Jan 23 - System Dynamics and Simulation Games (SLG)

From a macro perspective, introduction to system dynamics as an approach for modeling complex systems. Introduction to the core mechanisms behind classical SLGs that utilize system dynamics concepts, such as SimCity.

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Jan 28 - Swarm Intelligence and Emergent Intelligence

From a micro perspective, introduction to agent-based approaches as another method for performing simulations. Introduction to swarm intelligence, inspired by real-world examples (e.g., ants), and their simulation through collaborative and competitive agents. Introducing current advances in emergent intelligence with Large-language-Model agents and their limitations. Introducing the application behind modern simulation games such as Cities: Skylines, Civilization, and Anno.

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Jan 30 - Multi-Agent Learning

Step from the concept of game theories we built from the previous lectures, we explore methods to train agents to make decisions in the environment we created. Starting from reinforcement learning (RL), we will introduce multi-agent RL and explore the pros and cons of a variety of methods. Overview of advances in this field, including Deep Blue, AlphaGo, and Cicero.

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