Cognitive Assemblages

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COGNITIVE ASSEMBLAGES Sharpening machine sensibility for architectural design of spatial assemblages through Wave Function Collapse and Reinforcement Learning

Alessandro Mintrone University of Bologna


Introduction Theory overview

Is it possible connect, into the distributed lattice of decisions of the design process, sufficiently complex non-human cognitions capable of claiming part of the authorship, generating spaces, places and everything comprised in the larger spectrum of architecture?

In this page. Manus, robotic installation by Medeline Gannon, at the World Economic Forum.

Cognitive Assemblages


Artificial Neural Networks


Artificial Neural Networks Artificial Intelligence

In this page. AI classifiction scheme, according to Ian Goodfellow in his book Deep Learning Cognitive Assemblages


Artificial Neural Networks Structure

Artificial Neural Networks learn how to map an array of inputs into an array of outputs, passing thru a defined number of internal layers, each one composed by a defined number of units connected to the adjacent layers. What is learned during the training process are the weights of these connections. In this page. Neural network model with a single hidden layer Cognitive Assemblages


Artificial Neural Networks Example

In this page. Example of a classifier based on a Convolutional Neural Network Cognitive Assemblages


Artificial Neural Networks Latent Space

In this page. Representation of the internal latent space, visualizing categorial boundaries Cognitive Assemblages


Artificial Neural Networks Tools

High level features A neural network can deal with high level features, such as the overral shape of the head of the skin’s texture, capturing non-linear relationships between these features.

In this page. Two images generated within the project: This person does not exist. Cognitive Assemblages


Wave Function Collapse


Wave Function Collapse Overview

Entropy Analysys

Collapsing Point Selection

Possible Tiles [0, 1, 1, 0, ..., 1, 0]

Contraddiction

Tiles Selection

Diffusion

Algorithmic process

Tileset and resulting assemblage

Cognitive Assemblages


Wave Function Collapse Connection rules

Possible Tiles [0, 1, 1, 0, ..., 1, 0]

Contraddiction

Tiles Selection

Single tiles

Permutations

Contraddictions

Assemblage

Possible connections

Forbidden connections

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Wave Function Collapse Information diffusion

Information diffusion Tiles Selection

Diffusion

Set di tiles

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Tile Set 02 Tridimensional oriented

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Tile Set 02 Tridimensional oriented

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Tile Set 03 Tridimensional cubic

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Tile Set 03 Tridimensional cubic

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Tile Set 05 Tridimensional planar

Cognitive Assemblages


Tile Set 05 Tridimensional planar

Cognitive Assemblages


Reinforcement Learning


Reinforcement Learning Cognition and environment

With Reinforcement Learning the neural network learns from experience. Constructing a feedback-loop by acquiring informatins from the environment, selecting an action and, in this way, transforming the environment itself.

In this page. Feedback loop diagram of the agent interacting with the environment Cognitive Assemblages


Reinforcement Learning Cognition and environment

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In this page. AlphaGo, is the first computer program to defeat a professional Go player. The system combines Reinforcement Learning with a Montecarlo tree-search algorithm Cognitive Assemblages


Wave Function Collapse Intelligence

Entropy Analysys

Entropy Analysys

Collapsing Point Selection

Collapsing Point Selection

Possible Tiles

Possible Tiles

[0, 1, 1, 0, ..., 1, 0]

[0, 1, 1, 0, ..., 1, 0]

Contraddiction

Contraddiction

Tiles Selection

Tiles Selection

Diffusion

Neural Network

Diffusion

Algorithmic process

Neural Network inception

Cognitive Assemblages


Density

Gradient

Spatial Analysis

Spatial Analysis

1. Density 1 - |desiredDensity - currentDensity|

2. Gradient 1 - fieldValue

Cognitive Assemblages


Orientation

Structural Connectivity

Spatial Analysis

Spatial Analysis

3. Orientation allignedTiles / totalTiles

4. Structural Connectivity 1 - tilesUnderThreshold / totalTiles

Cognitive Assemblages


Spatial Connectivity

Planar Connectivity

Spatial Analysis

Spatial Analysis

5. Spatial Connectivity 1 - tilesUnderThreshold / totalTiles

6. Planar Connectivity 1 - tilesUnderThreshold / totalTiles

Cognitive Assemblages


Machine Learning Rete neurale

3 hidden layers

Input

output

0, 0, 1, . . . 0, 1

0, 0, 1, . . . 0, 1

256 units

256 units

256 units

Neural Network Model

Cognitive Assemblages


Machine Learning Analisi e visualizzazione

Parameters visualization on Tensorboard

Cognitive Assemblages


Training Heuristic comparison

The Neural Network obtains not only better results in terms of reaching a target density, but also determines non-linear behaviors that led to pattern generation.

Porbabilistic Heuristic Required density: 50% Actual density: 76%

Trained Neural Network Required density: 50% Actual density: 54%

Cognitive Assemblages


Training Density

Target value

Analysis Parameters

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Training Orientation

Target value

Analysis Parameters

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Training Connectivity

Target value

Analysis Parameters

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Training Density + Connectivity

Target value

Analysis Parameters

Cognitive Assemblages


Training Density + Orientation

Target value

Analysis Parameters

Cognitive Assemblages


Training Orientation + Connectivity

Target value

Analysis Parameters

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Training Global

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Discrete Assemblages


Assemblages Fabrication and automation

In this page. Designed by Moshe Safdiefor the 1967 Expo in MontrĂŠal, the Habitat use prefabricated parts and a combinatorial logic for spatial generation

Cognitive Assemblages


Assemblages Fabrication and automation

Ăˆ possibile inserire, nella rete di decisioni del processo progettuale, cognizioni non-umane sufficientemente complesse da assumere in parte la responsabilitĂ della creazione, per generare spazi, luoghi e ogni altro esito che è possibile chiamare architettura?

In questa pagina Installazione di Gilles Retsin per la biennale di architettura di Tallin (TAB) del 2017. Cognitive Assemblages


Assemblages Parts and connections

In this page. Case study, example of design and connection rules of the selected tileset

Tileset

Connection rules: corners

Connection rules: horizzontal parts

Connection rules: diagonal parts

Connection rules: vertical parts Cognitive Assemblages


Assemblages Comparative Analysis

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Assemblages Comparative Analysis

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Assemblages Comparative Analysis

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Assemblages Analysis overview

Voids analysis

Overview and analysis parameters

Connectivity Analysis

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Assemblages Analysis overview

Plan view

Autonomously generated internal views

Section view

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Assemblages Analysis

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Voids

Connectivity

Plan

Section


Assemblages Analysis

Cognitive Assemblages

Voids

Connectivity

Plan

Section


Assemblages Analysis

Cognitive Assemblages

Voids

Connectivity

Plan

Section


Assemblages Analysis

Cognitive Assemblages

Voids

Connectivity

Plan

Section


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


Cognitive Assemblages


Cognitive Assemblages


Cognitive Assemblages


Cognitive Assemblages


Cognitive Assemblages


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


Case Study

Cognitive Assemblages


COGNITIVE ASSEMBLAGES Alessandro Mintrone University of Bologna alessandro.mintrone@hotmail.com


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