Course Outline

I. Introduction to Emergence and the Decentralized Mindset

Introduce ideas of simple rules giving rise to complex patterns, system behaviors, cyclical behavior, stable and unstable patterns, equilibria. Diversity of real world examples. Contemporary applications..

II. Artificial societies

Simple models of social worlds. Pedestrians, self-organizing neighborhoods, parties; gossip, voting.

III. Multi-agent Models in biology and ecology

Slime mold, rabbits and foxes (simulation solutions to Lotka-Volterra equations), genetic drift, mimicry, flocking, disease/contagion,

IV. Multi-agent models in physics, chemistry and mathematics

Chemical reactions, gasses, heat, gravitation, enzyme kinetics, crystallization, Maxwell’s Demon, annealing, radioactive decay, cellular automata, Turing Machine, fractals, Mandelbrot set, stochastic processes, random walks

V. Multi-agent models in politics and economics

Hawks and doves. Markets. Voting paradox. Flocking and public opinion. Formation of cities/states, altruism, cooperation, segregation, demographics, prisoner's dilemma, tragedy of the commons, voting paradox

VI. Using multi-agent models to produce art

Diffusion Graphics, Fireworks, Kaleidoscope

VII. Simulations and the real world: applications and verification