Programming Complexity: Modeling Complex Systems with Ruby and React
summary
Agent-based simulations run in Ruby/React (live via Puma) on a 36x36 grid. Cultural model uses 6 features × 16 traits per cell, measures average feature distance, uniques and change rate, and produces a few dominant cultures with distance falling but not to zero and early dominance not guaranteed. Segregation model checks every cell with a neighbor-threshold, vacant-cell % and policy caps; segregation appears even for weak same-race preference. Volunteer dilemma yields ~62% at 3 agents and shows volunteering probability falls as agent count rises; lowering individual cost increases volunteering.
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chapters (6)
- 0:00Start
- 10:35What do we want to measure?
- 19:00Parameters
- 28:10Payoff matrix for a 2-player game
- 28:54Mixed strategy Nash equilibrium
- 29:12For an N-player game
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