In Part I. Introduction

I-3. Introduction to agent-based modeling

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I-5. The fundamentals of NetLogo

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In Part II. Our first agent-based evolutionary model

II-1. Our very first model

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II-2. Extension to any number of strategies

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II-3. Noise and initial conditions

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II-4. Interactivity and efficiency

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• nxn-imitate-if-better-noise-efficient-but-more-than-once-profiler.nlogo
• nxn-imitate-if-better-noise-efficient-played-profiler.nlogo
• nxn-imitate-if-better-noise-efficient-tick-I-played-last-profiler.nlogo
• nxn-imitate-if-better-noise-efficient-tick-I-played-last-and-other-players-profiler.nlogo
• nxn-imitate-if-better-noise-efficient.nlogo (after exercise 5)

In Part III. Spatial interactions on a grid

III-1. Spatial chaos in the Prisoner’s Dilemma

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III-2. Robustness and fragility

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III-3. Extension to any number of strategies

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III-4. Other types of neighborhoods and other decision rules

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In Part IV. Games on networks

IV-1. The nxn game on a random network

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IV-2. Different types of network

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IV-3. Implementing network metrics

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IV-4. Other ways of computing payoffs and other decision rules

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In Part V. Agent-based models vs ODE models

V-2. A rather general model for games played in well-mixed populations

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• nxn-games-in-well-mixed-populations.nlogo

V-3. Mean Dynamics

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