Meta-Evolver is a tool for a visual representation of the various dynamic environment models that correlate in multi-layered system. Meta-Evolver provides the environment for testing dynamic spatial adaptation, where the environment is composed of algorithms and parametric definitions. This research uses advanced AI methods (meta-learning) and cutting-edge technologies including immersive environments and virtual reality (VR) to offer innovative methods of architectural creation. The ability to continuously learn and adapt from limited experience in a dynamic environment is an important milestone on the path towards building interactive spaces in modern architecture. We developed the tool Meta-Evolver for testing spatial adaptation in dynamic environments and integrated the ability for interaction with a human user.
Meta-Learning Multi-Agent System Diagram
*This research was supported by CTU grant SGS19/117/OHK1/2T/15.
Technical Documentation
SW dependencies
Blender 2.8
dependencies AddRoutes OSC, MIDI
install http://www.jpfep.net/pages/addroutes/ https://github.com/JPfeP/AddRoutes
AddRoutes.zip enable add-on in Blender preferences
NodeOSC.zip https://gumroad.com/avantcontra
Several core modules: –Blender Eevee Engine: responsible for real-time rendering –NodeOSC, AddRoutes Blender addons: responsible for OSC data sending and receiving –PureData: responsible for sound processing, NN, BCI –BugOSC: OSC controller
