0. Introduction

0.2. Introduction to agent-based modeling

0.2-schelling-sakoda.nlogo

0.4. The fundamentals of NetLogo

0.4-schelling-sakoda-simple.nlogo

1. Our first agent-based evolutionary model

1.0. Our very first model

1.0-2×2-imitate-if-better.nlogo

1.1. Extension to any number of strategies

1.1-nxn-imitate-if-better.nlogo

1.2. Noise and initial conditions

1.2-nxn-imitate-if-better-noise.nlogo

1.3. Interactivity and efficiency

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

2. Spatial interactions on a grid

2.0. Spatial chaos in the Prisoner’s Dilemma

2.0-2×2-imitate-best-nbr.nlogo

2.1. Robustness and fragility

2.1-2×2-imitate-best-nbr-extended.nlogo

2.2. Extension to any number of strategies

2.2-nxn-imitate-best-nbr.nlogo

2.3. Other types of neighborhoods and other decision rules

2.3-nxn-imitate-best-nbr-extended.nlogo

3. Games on networks

3.0. The nxn game on a random network

3.0-nxn-imitate-if-better-rd-nw.nlogo

3.1. Different types of network

3.1-nxn-imitate-if-better-networks.nlogo

3.2. Implementing network metrics

3.2-nxn-imitate-if-better-networks-metrics.nlogo