Course OutlineI. Introduction to Emergence and the Decentralized MindsetIntroduce 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 societiesSimple models of social worlds. Pedestrians, self-organizing neighborhoods, parties; gossip, voting. III. Multi-agent Models in biology and ecologySlime mold, rabbits and foxes (simulation solutions to Lotka-Volterra equations), genetic drift, mimicry, flocking, disease/contagion, IV. Multi-agent models in physics, chemistry and mathematicsChemical 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 economicsHawks 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 artDiffusion Graphics, Fireworks, Kaleidoscope VII. Simulations and the real world: applications and verification |
college 60v (2009)