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Can we capture the unpredictable evolutionary and emergent properties of nature in software? Can understanding the mathematical principles behind our physical world help us to create digital worlds? This class focuses on the programming strategies and techniques behind computer simulations of natural systems. We explore topics ranging from basic mathematics and physics concepts to more advanced simulations of complex systems. Subjects covered include physics simulation, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. Examples are demonstrated using the p5.js environment with a focus on object oriented programming.
Video featuring original artwork in P5.js by:
Particle Equalizer #1 by Sehyun Kim
Look at me! by Muqing Niu
Dancing Spring by Yue Hu
FireWork by Yue Hu
Nature Of Code final at ITP by Joe_Mango
Nature of Code - midterm by Marcela Nowak
Sound And Motion Coding by Marcela Nowak
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Session 1: Introduction / Overview
In this session we’ll review the basics of p5.js and get everyone up and running with posting sketches online. We’ll look at how object-oriented programming works in JS and create simple sketches of objects moving around a canvas. Session 2: Vectors / Forces
This session will look at the concept of a vector and implement sketches using a p5.Vector object. By creating objects with vectors for position, velocity, and acceleration, we’ll build a simple “hello world” physics engine. Session 3: Steering Behaviors
This session, we’ll examine a special kind of force (pioneered by Craig Reynolds) — a steering force — that moves an object according to its own goals or desires. Examples are wandering, seeking a target, path following, obstacle avoidance, and more. We’ll then look at how group behaviors can be simulated by combining multiple steering behaviors according to local interactions between objects. Session 4: Fractals
In this session we will cover the concept of a fractal and look at ways of generating fractal patterns with code. Session 5: Genetic Algorithms
This session will look at the key concepts of Darwinian evolution — variation, selection, heredity — and examine how they can be applied in a computer simulation.
