All Videos Tagged intelligence (Grasshopper) - Grasshopper

Crow Tutorial1: Neural Sensing and Control in Grasshopper

2017-10-10T13:43:45.819Z

Supervised learning is a branch of machine learning in which a mapping function is programmed into a neural network by exposing examples to the network (training).
This tutorial shows how to use the plug in Crow to classify certain environmental states (based on sensor data) and relate them to a parametric model, hence a neural network classifies sensor states and maps them to respective parametric outputs.

All the files can be found here:
https://github.com/HeinzBenjamin/Crow/tree/master/Study%20Material/Supervised%20Learning/Sensor_classification

...and here:
http://www.food4rhino.com/app/crow-artificial-neural-networks

Flock Based Spatially Distributed Open-Source Customisable Plywood Structure

2017-10-07T17:30:32.111Z

Master Thesis | TUC Postgraduate Program

Exploring the spatial distribution of a group of customisable plywood structures to be used as students' work spaces at the area of Technical Univerisity of Crete. Inspired by Greg Reynold's BOIDS and Swarm Intelligence, this project attempts to design a code that simulates flocking behaviours on site. With no apparent, at this point, optimization goal, but to study emerging plan patterns and self organization of the individual units.

Software | Rhino Grasshopper, Gismo, Quelea, Galapagos, Human UI

Rainbow Dog | 2-Dimensional Self-Organizing Maps using Crow in Grasshopper

2016-06-20T23:46:30.846Z

This videos shows the use of the plug-in Crow for Grasshopper in Rhino5. It employs artificial neural networks - specifically a 2-dimensional Kohonen layer, known as self-organizing maps - to fit data vectors of three, four or five dimensions through a set of given training data.
Crow is an extension of NeuronDotNet.dll developed by the NeuronDotNetTeam

Get Crow here: http://www.felbrich.com/projects/Crow/Crow.html

Swarm intelligence Cast

2015-11-21T04:01:43.379Z

Using Boid library by Ján Pernecký, Anemone by Mateusz Zwierzycki and Marching Cubes by David Stasiuk

www.arturodelafuente.com

Swarm Intelligence XV: Stimergic Pheromone Paths

2015-01-30T11:29:56.248Z

Using boids to track pheromone paths. 2 500 boids travel on dynamic vector fields. There is no interaction between boids, but every agent leaves a trail, changing parameters of the vector on the field. In every iteration vector field is read by boids and use as an emerging pattern of movement. Stimergic patterns occur as a result.