AI Sprawl

Collaborative AI Human + AI Form Workshop
Summer 2021
w/ Kiran Kastury


“AI Sprawl” is a machine learning experiment based on behavioral conditioning. Reward and punishment are utilized to encourage success of designed aggregative behaviors. Collision, avoiding collision, applied or unapplied gravity, only interlocking, as well as designed rotations and interchanges of stacking housing units and urban artifacts, are studied as variables of a training process in pursue of unexpected, yet controlled, intelligent aggregations.

Made in Unity using machine learning workflows.

Type:               Workshop
Institution:    ACADIA 2021 Realingments
Instructors:   Chien-hua Huang &  Zach Beale
Research:      Machine Learning, AI, Unity.

1. Vetical stacking over topography intent results.
2. Spread stacking over ground and topography intent results.
3. Applied and unapplied collision and gravity stacking experiments. 

-Sound On-