Genetic algorithms are a form of machine learning. They allow machines to adapt to different circumstances over time by translating Darwin's theory about human evolution into code. In this project the very same algorithm is used to dictate human movement.
Find a detailed project page on genetic-dance-algorithm.leoneckert.com.
Video: The Genetic Dance Algorithm Performance
The script of the performance seen below is generated by the Performance Simulation Program (shown further below), then rehearsed and brought back into a human environment. The goal, in this case, was a 'direct' quality of movement which it took 10 generations to reach.
Video: Performance Simulation Program
Each dancer has an individual DNA in the form of a sequence of numbers that refer to movements. The DNA dictates their performances. In the beginning, the DNAs' numbers are random and so is the movement on stage. The user selects a goal for the performance in the top right corner of the program: this defines the desired movement quality building upon theories of Laban Movement Analysis
If you are curious, please find more information here.
This project was shown as part of the Codame Art+Tech "Movement" Festival in San Francisco, 2015.
Genetic Dance Algorithm at the Codame Art+Tech Festival in San Francisco, 2015.