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Generative Design Research Methodology

Dr. Ir. Pirouz Nourian

Assistant Professor of Design Informatics

Department of Architectural Engineering & Technology

Faculty of Architecture and Built Environment

PhD in Design Informatics, MSc in Architecture, BSc in Electrical Engineering (Major in Control Systems Engineering)

Theoretical underpinnings of practice for systematic deduction and exploration in design

1

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Theme: Computational Design/Generative Design

[Mathematical] Design Optimization

Computational Topology Optimization

for Designing Compression-Only

Masonry/Earthy Buildings

Background and aim:

Masonry/Earthy structures can be made with sustainable

materials while offering strong structural properties,

especially if designed as compression-only structures.

Optimal masonry structures might take complex geometric

shapes that present architectural design and structural

validation challenges. We aim to develop computational

methods & tools for automatic generation of valid structural

forms.

Research question:

How to computationally generate valid designs for

compression-only brick/masonry structures?

Design objective:

To design and prototype a topology optimization tool for

designing masonry structures.

Methods:

•Topology Optimization (req. Calculus, Linear Algebra, etc.)

•Computational Topology & Geometry

•Finite Element Method

•Computer Programming (Python)

Image Credits: Rick van Dijk, thesis project, 2019-2020

Image Credits: Idil Gumruk, thesis project, 2017-2018

Image Credits: Karim Daw, Shervin Azadi, Pirouz Nourian, Hans Hoogenboom

Image Credits: Ivan Avdic, thesis project, 2018-2019

Latest Version: https://genesis-lab.dev/topics/computational-topology-optimization/ 2

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

3

Computational Shape Optimization

for Designing Compression-Only

Masonry/Earthy Buildings

Background and aim:

Masonry/Earthy structures can be made with sustainable

materials while offering strong structural properties,

especially if designed as compression-only structures.

Optimal masonry structures might take complex geometric

shapes that present computational design and structural

validation challenges. We aim to derive optimal shapes

directly based on a gradient descent optimization procedure

as a constructible structure.

Research question:

How to computationally find optimal catenary forms and

approximate them with modular brick/block structures?

Design objective:

To design and prototype a computational finite element

modeler for masonry structures.

Methods:

•Shape Optimization (req. Calculus, Linear Algebra, etc.)

•Computational Geometry & Topology

•Finite Element Analysis

•Computer Programming (Python or C#) Image Credits: Karim Daw, Shervin Azadi, Pirouz Nourian, Hans Hoogenboom

Image Credits (EARTHY 2019-2020): Yarai Zenteno, Fahriba Mustafa, Patrattakorn

Wannasawang, Akash Changlani, Elisa Vintimilla, Shasan Choksi

Latest Version: https://genesis-lab.dev/topics/computational-shape-optimization/

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Grammatical] Design Customization

Topological Shell Design

For Modular Approximation of Optimal

Catenary Shells

Image Credits (EARTHY 2019-2020):

Nikoleta Sidiropoulou, Hans Gamerschlag, Noah van den Berg,

Hamidreza Shahriari, Rick van Dijk, Maximilian Mandat

Image Credits: Karim Daw, Shervin Azadi, Pirouz Nourian, Hans Hoogenboom

Background and aim:

Masonry/Earthy structures can be made with sustainable

materials while offering strong structural properties,

especially if designed as compression-only structures.

Optimal masonry structures might take complex geometric

shapes that present constructability challenges. We aim to

develop combinatorial methods for approximating optimal

shells with modular blocks.

Research question:

How to approximate optimal shell structures as

an assembly of modular blocks for easy construction?

Design objective:

To design and prototype a combinatorial process

for modular polyhedral shape approximation.

Methods:

•Geometric Design and Tessellation

•Computational Geometry (optionally in Python)

•Structural Design and Mechanics

•Material Science

Latest Version: https://genesis-lab.dev/topics/topological-shell-design/ 4

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Grammatical] Design Customization

Combinatorial Surface & Solid Design

Polygonization and Polyhedralization

Background and aim:

In digitalization and industrialization of housing production, it

is a challenge is to provide affordable quality solutions at

scale. Modularity of building products can provide for

efficient production as well as diversification of the building

stock by means of combinatorial variations. We aim to

develop methods in computational geometry for mass-

customization of housing design-build processes based on

standardised architectural modules.

Research question:

How to design the Stereotomy of a limited set of blocks to

provide a large combinatorial surface/solid design space?

Design objective:

To design and prototype a computational and participatory

process for modular polygonal/polyhedral shape design.

Methods:

•Geometric Design and Tessellation

•Topological Polygonization & Polyhedralization

•Iso-surface Algorithms (Python or C#)

•Automatically writing Open-Standard Data Models

Image Credits: Marian42 and Oskar Stalberg

Image Credits: Hugo van Rossum,, Maren Hengelmolen, Liva Sadowska, Sander

Bentvelsen, Spatial Computing Architectural Design Studio - 2020 - CUB3D

Latest Version: https://genesis-lab.dev/topics/combinatorial-surface-solid-design/ 5

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Gamification of Generative Design

For Combinatorial Generation of

Modular Designs

Background and aim:

Participatory design is a necessity especially when multiple

stakeholders are to be involved in design and operation of

a building. Gamification of design into a combinatorial

configuration process provides an interactive medium for

stakeholders to be included in decision-making, explore the

vast possibilities of modular systems, and easily co-create

valid designs.

Research question:

How to formalize spatial design process as a participatory

game?

Design objective:

To design and prototype toolsets and tile-sets for

combinatorial design games aimed at modular assemblies.

Methods:

•Geometric Design and Tessellation

•Computational Topology & Geometry (optionally in Python)

•Gamification and Playful Learning

•Ergonomics

•Participatory Architectural Spatial Design

Image Credits: the Blookhood Game, Jose Sanches

Image Credits (EARTHY 2019-2020):

Alessandro Passoni, Alessio Vigorito, Fredy Fortich Kiana Mousavi, Stephanie Moumdjian

Image Credits: the Monument Valley Game

Latest Version: https://genesis-lab.dev/topics/gamification-of-generative-design/ 6

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Generative Solar-Climatic Configuration

Mathematical Derivation of Building

Envelopes as to Climatic Requirements

Image Credits: Samaneh Rezvani, Pirouz Nourian

Image Credits: Shervin Azadi, project Go-Design

Image Credits (Spatial Computing, 2018-2019):

Fé van Lookeren Campagne, Max Ketelaar, Ruben Schonewille

Background and aim:

Early design decisions have great influence on final energy

performance and comfort of buildings. Proper consideration

of such influences requires using simulation engines. The

existing simulation methods can be too data demanding

and slow for early-stage computational design explorations

(e.g. in optimization loops or form-finding). The aim of this

project is to devise and prototype fast and design-friendly

simulation methods for generative design of optimal

envelopes.

Research question:

How to adapt and develop direct sunlight and view-shed

simulation methods for generation of optimal envelopes?

Design objective:

To design and prototype a suite of generative methods for

fair and optimal provision of solar irradiation, radiative

cooling potential and view shed.

Methods:

•Spatial Computing (Computational Geometry & Linear Algebra)

•Physical Analysis of Light and Principles of Naturally Lit Design

•Computer Programming (Python or C#)

Latest Version: https://genesis-lab.dev/topics/generative-solar-climatic-configuration/ 7

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Latest Version: https://genesis-lab.dev/topics/generative-configuration-design/ 8

Background and aim:

Modeling the spatial design space discreetly will allow us to see

the configuration problem of a building as a discrete decision-

making problem. This will provide for ex-ante assessment of

various criteria that influence the functionality of a building in

terms of accessibility/visibility-related factors. The aim of the

research is to devise a systematic way of configuring

buildings in 3D to optimally meet functional requirements

pertaining to such factors etc.

Research question:

How to configure a building procedurally given a program of

requirements, accessibility, and daylight requirements and

complex site constraints?

Design objective:

To design and implement a computational 3D layout

methodology.

Methods:

•Architectural Engineering

•Multi-Criteria Decision Analysis

•Computational Topology and Graph Theory

•Computer Programming (Python/C#)

Generative Configuration Design

Feed-Forward 3D Configuring as to

Spatial Qualities and Requirements

Image Credits (Spatial Computing, 2018-2019):

Fé van Lookeren Campagne, Max Ketelaar, Ruben Schonewille,

optimal

design

Variant 3

Variant 1

Variant 2

Image Credits: Shervin Azadi, project Go-Design

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Latest Version: https://genesis-lab.dev/topics/space-optimization/

Space Optimization

Spatial Re-Configuration through

Mathematical Optimization

Image Credits: Spatial Computing Architectural Design Studio - 2020 - CUB3D

Image Credits: Facility Management Network (link)

Image Credits: Spatial Computing Architectural Design Studio - 2020 - Green Valley

Background and aim:

The spatial configuration of a building can be abstracted as a

network of functional spaces that influences the functionality

of a building in terms of movements of the occupants, logistic

efficiency, feasibility of social distancing, safety of routing,

and security. The aim of the research is to propose a

systematic way of configuring buildings in 3D to optimally

meet functional requirements pertaining to such factors etc.

Research question:

How to optimize the allocation of spaces in a building based on

a program of requirements, and a set of criteria concerning

accessibility and visibility?

Design objective:

To design and implement a computational 3D layout

methodology.

Methods:

•Operations Research (Mathematical Optimization)

•Quadratic Assignment Problem

•Computational Topology and Graph Theory

•Computer Programming (Python/C#)

9

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Latest Version: https://genesis-lab.dev/topics/ai-configurators/

AI Configurators

3D Layout via Reinforcement Learning

Image Credits: Pedro Veloso, Ramesh Krishnamurti, An Academy of Spatial Agents

Image Credits: Shervin Azadi, Pirouz Nourian, GoDesign

Background and aim:

Spatial qualities heavily depend on the configuration of spaces.

In this research project, we develop computational agents

that configures the space within a voxelated envelope while

ensuring spatial qualities such as daylight, accessibility to

other spaces, etc., via Multi-Criteria Decision Analysis. Each

computational agent utilizes Reinforcement Learning to

understand the inter-relation of global spatial quality criteria

with local spatial decisions.

Research question:

How to train an ensemble of artificial agents to make local

spatial decisions to attain high global spatial qualities?

Design objective:

To design and implement a computational 3D layout

methodology using DRL.

Methods:

•Deep Reinforcement Learning (DRL, Artificial Intelligence)

•Multi-Criteria Decision Analysis (MCDA)

•Topology Optimization

•Computer Programming (Python/C#)

10

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Background and aim:

Early design decisions have great influence on final energy

performance and comfort of buildings. The costs of

installation, maintenance, and the eventual replacement of

solar panels cannot be ignored in the financial outlook of a

building. This project aims to develop procedures for

including such financial considerations in addition to

architectural factors in optimal configuration of solar panels.

Research question:

How to configure an optimal array of photovoltaic cells on a

building envelope so as to maximize solar electricity yield

subject to architectural and economic constraints?

Design objective:

To computationally configure an optimal array of photovoltaics

on a building envelope.

Methods:

•Spatial Computing (Computational Geometry & Linear Algebra)

•Ladybug Recipes (environmental simulation workflows)

•Computer Programming (Python)

Maximizing Solar Electricity Yield

Computational Derivation of Configuration

of Photovoltaic Panel Arrays on Buildings

Image Credits: Tolga Ozdemir, MSc Thesis Project, 2019-2020

Latest Version: https://genesis-lab.dev/topics/maximizing-solar-electricity-yield/ 11

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Latest Version: https://genesis-lab.dev/topics/open-source-digital-twinning/

Open-Source Digital Twinning

Web-based Platforms for Spatial

Decision Support Systems

Image Credits: Aditya Soman & Shervin Azadi,

Image Credits: Brainport Development

Background and aim:

The decisions made on the spatial configurations and

distributions in the built environments (urban or rural

developments) have enormous impacts on the

environmental, economic, and societal sustainability of the

planet. The aim of the project is to provide mechanisms for

modelling the impacts of such spatial decisions using open-

source libraries and geo-spatial data to simulate complex

what-if scenarios for transparent and participatory decision-

making.

Research question:

How to make digital twins for spatial decision support using

open-data and open-source libraries?

Design objective:

To design and implement a computational framework for geo-

spatial digital twinning geared towards decision analysis.

Methods:

•geo-spatial computing (geo-informatics)

•geo-spatial analysis (spatial queries)

•geo-spatial Database Management Systems (DBMS)

•Computer Programming (Python/C#)

Image Credits: Brainport Development

Image Credits: Maartje Damen & Shervin Azadi

12

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Latest Version: https://genesis-lab.dev/topics/participatory-design-in-digital-twins/

Participatory Design in Digital Twins

Web-based Platforms for Participatory

Spatial Decision Making

Image Credits: Brainport Development

Image Credits: Shervin Azadi, EquiCity Game

Image Credits: Aditya Pravin Soman

Background and aim:

The decisions made on the spatial configurations and

distributions in the built environments (urban or rural

developments) directly influences the life of multiple

stakeholders. The aim of the project is to provide

mechanisms for involving different stakeholders in the spatial

decision making process and facilitating their negotiations

through Spatial Decision Support Systems (SDSS).

Research question:

How to make digital twins for participatory spatial decision

making?

Design objective:

To design and prototype a Multi-Actor and Multi-Criteria Spatial

Decision Support System.

Methods:

•geo-spatial computing (geo-informatics)

•geo-spatial analysis (spatial queries)

•geo-spatial Database Management Systems (DBMS)

•Computer Programming (Python/C#)

13

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Latest Version: https://genesis-lab.dev/topics/human-space-interaction-modelling/

Background and aim:

Humans and their environment have a reciprocal relation: we

constantly build and change our environment and our

environment shapes the way we use the space and navigate

through it. However, we still lack a comprehensive

understanding of how different spatial qualities affect legibility

of space and its ergonomy.

Research question:

How can we objectively assess the cognitive and ergonomic

comfort of a spatial configuration?

Design objective:

To design and develop a computational framework for

assessing the cognitive/ergonomic spatial qualities.

Methods:

•Spatial Computing (Computational Geometry & Linear Algebra)

•Mathematical Analysis of Visibility

•Deep Neural Networks (DNN, Artificial Intelligence)

•Computer Programming (Python or C#)

Human-Space Interaction Modelling

Spatial Cognition and Space Navigation

Image Credits: Z. Wang et al., 2019, doi: 10.1016/j.buildenv.2019.04.035.

14

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Mathematical] Design Optimization

Latest Version: https://genesis-lab.dev/authors/anastasia-florou/ 15

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Grammatical] Design Customization

Latest Version: https://genesis-lab.dev/authors/selina-bitting/ 16

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Latest Version: https://genesis-lab.dev/authors/aditya-soman/ 17

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

[Gamified] Participatory Design

Latest Version: https://genesis-lab.dev/authors/beza-bekele/ 18

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Generative Design

Generative Design

:=

{Simulation-Driven, Gradual, Transparent, Explainable, and Reproduceable}

‘Combinatorial Generation’

of

{a Navigable Catalogue of Valid/Optimal Design Alternatives}

Image Credit: Genesis Laboratory of Generative Systems and Sciences 19

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Relevance of Generative Design

The Scientific Method is

a meta-level term to describe research methods that can derive objectively verifiable and reproducible

knowledge. This lecture discusses the aim, the theoretical underpinnings, and the practice, of the scientific

method in systematic exploration/itemization and/or systematic deduction/derivation in architectural

design given measurable functional or performance objectives and physical constraints.

ethos

Open-Science, Mathematical Transparency, Scientific Discovery, Participatory Decision-Making,

Explainable Artificial Intelligence, Modularity, Reproducibility, Critical Thinking, Intellectual Freedom

raisons d'être

Efficacy, Equity, Sustainability, Circularity, Quality of Life (w.r.t. Ergonomics & Human Factors)

20

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Why Generative Design?

Architectural Engineering

∋

{Engineering, Human Factors, and Ergonomics}

Image Credit: GoDesign Generative Design Framework 21

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Why Generative Design?

Image Credit: Genesis Laboratory of Generative Systems and Sciences 22

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Methodology?

Research Methodology >σ𝐢𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐌𝐞𝐭𝐡𝐨𝐝𝐢

23

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Design Science?

Research MethodologyDesign ResearchGenerative Design

Design Science

Generative Design Research Methodology

24

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Generative Design≔Systematic (methodical) processes for synthesis of plans, configurations and forms

Generative Design Methods, Techniques, and Products

Grammatical Methods

Mathematical Methods

Systematic Processes

Networks

Graphs

Plans

Layouts

Topologies

Configurations

Shapes

Geometries

Forms

Serious Games

Synthesis

Exploration/Itemization

Deduction/Derivation

for of

,

,

, , and

, and

, and

METHODS TECHNIQUES PRODUCTS

25

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Generative Design≔Systematic (methodical) processes for synthesis of plans, configurations and forms

Generative Design Methods, Techniques, and Products

Grammatical Methods

Mathematical Methods

Systematic Processes

Networks

Graphs

Plans

Layouts

Topologies

Configurations

Shapes

Geometries

Forms

Serious Games

Synthesis

Exploration/Itemization

Deduction/Derivation

for of

,

,

, , and

, and

, and

METHODS TECHNIQUES PRODUCTS

Design

Engineering

Mathematics

abstract concrete

26

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Computational Design Paradigms

•Dorst, Kees. "On the problem of design problems-problem solving and design expertise." Journal of design research 4.2 (2004): 185-196.

•Lawson, Bryan. "Schemata, gambits and precedent: some factors in design expertise." Design studies 25.5 (2004): 443-457.

•Simon, Herbert A. The sciences of the artificial. MIT press, 2019.

•Schön, D. (1938). The reflective practitioner. New York, 1983.

•Nourian, P. “Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,” Doi.Org, vol. 6, no. 14. pp. 1–348, 2016.

•Nourian, P., How to write a thesis? A Generative Design Graduate Studio Guidebook. (2019). Delft University of Technology, Faculty of Architecture and Built Environment, Department

of Architectural Engineering and Technology. DOI: 10.6084/m9.figshare.11987328

•S. Azadi and P. Nourian, “Collective Intelligence in Generative Design: A Human-Centric Approach Towards Scientific Design,” BouT: Periodical for the Building Technologist, vol. Generative Design, no. 76,

pp. 7–16, Apr. 2021. doi: 10.13140/RG.2.2.15295.84642. [URL]

•S. Azadi and P. Nourian “GoDesign - A modular generative design framework for mass-customization and optimization in architectural design,” 2021. Accessed: Aug. 16, 2021. [Online]. Available:

http://papers.cumincad.org/cgi-bin/works/paper/ecaade2021_263 [URL]

•P. Nourian, S. Azadi, H. Hoogenboom, S. Sariyildiz, Earthy: Generative Design for Earth and Masonry Architecture, DOI: 10.13140/RG.2.2.28390.65607, [URL]

“Design as a Reflective Practice” (Schon, 1983) “Design as Rational Problem Solving” (Simon, 1996)

Procedural Design

Computational Design

Creative Design Generative Design

Parametric Design Combinatorial Design

Continuous Variations Discrete Variations

Inherently Analog Inherently Digital

Feed-back Optimization Feed-forward Optimization

Real Parameters (ℝ3)Integer Parameters (ℤ3)

Geometric Variation/Evolution Topological Variation/Evolution

Integrated Products Modular Products

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Scientific Paradigms

More information: https://www.thwink.org/sustain/glossary/KuhnCycle.htm

The Structure of Scientific Revolutions, Thomas Kuhn

Image credit: http://scienceprogress.org/wp-content/uploads/2013/01/DuckRabbit_full.gif

Loosely speaking,

Scientific Paradigms≃Scientific Worldviews

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Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Co-Existing Scientific Paradigms

Rabbit

Duck

e.g. in humanities

behaviourism in psychology versus cognitivism in psychology

Loosely speaking,

Scientific Paradigms≃Scientific Worldviews

More information: https://www.thwink.org/sustain/glossary/KuhnCycle.htm

The Structure of Scientific Revolutions, Thomas Kuhn

Image credit: http://scienceprogress.org/wp-content/uploads/2013/01/DuckRabbit_full.gif

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Scientific Revolutions

Aristotelian, Newtonian, Einsteinian

More information: https://www.thwink.org/sustain/glossary/KuhnCycle.htm

The Structure of Scientific Revolutions, Thomas Kuhn

30

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Scientific Revolutions

Aristotelian, Newtonian, Einsteinian

Methodologically

exemplified in both Macro-

scale theories of Albert

Einstein (relativity) and

Micro-scale theories of

Niels Bohr (quantum

physics). Although

competing for establishing

‘a theory of everything’,

they both have a similar

theoretical approach:

Mathematics and

Computation are the

drivers and the methods

of discovery. Models are

synthesized to

investigate complexity.

Theoretical Physics is the

best example.

Based on the writings of

Ptolemy, Aristotle, Plato:

Science was considered

as a branch of theology,

assuming a duality of

‘ideal/divine forms’ and

the material world. Earth

was the centre of a static

universe. Medieval Times.

Started with the Scientific Revolution,

pioneered by Nicolaus Copernicus,

Galileo Galilei, and flourished in the

Renaissance, culminated in the works

of Isaac Newton and Rene Descartes:

Science is defined as a methodical

practice in pursuit of objective

explanations and justifications for

observations. Earth is a planet in a

material universe. Renaissance &

Enlightenment Era: still dominant in

earthy applications.

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Methodology

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Design Research can be described as the field of study dealing with (Cross, 1999):

•Design Epistemology: that is about studying [processes of acquisition of] design knowledge and ‘how

designers think’*(Lawson, 1980) and the nature of their so-called tacit knowledge, knowhow, and

Experience.

•Design Praxeology: that is about how designers work in practice, how the design process proceeds

and what is/could be the role of design, representations, tools, and media in designing

•Design Phenomenology: that is about studying the nature of what is produced in designing, mainly

about form and configuration studies (conventionally known as architectural or urban morphology)

*Design Epistemology in Generative Design is mostly concerned with physics-based mathematical notions of

functionality or performance rather than the social ways of learning the so-called tacit knowledge of design.

Cross, N., 1999. Design Research as a Disciplined Conversation. Design Issues, 15(2), pp. 5-10.

Lawson, B., 1980. How designers think. 4th, 2005 ed. Burlington: Architectural Press, Elsevier.

Horvath, I., 2004. A treatise on order in engineering design research. Research in Engineering Design, 15(3), pp. 155-181.

Nourian, P. 2016, Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,, vol. 6, no. 14. pp. 1–348,

2016.

Design Research

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Design Research

Methodology

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

“The term methodology refers to ‘a structured collection of methods’, in the same way that the

term technology means ‘a structured collection of techniques’. What distinguishes a research

methodology from a mere collection of methods is a set of theoretical underpinnings, which

can be considered as ‘the theory of the methods’ (Horvath, 2004).”(Nourian, 2016)

Research Methodology

Horvath, I., 2004. A treatise on order in engineering design research. Research in Engineering Design, 15(3), pp. 155-181.

Nourian, P. 2016, Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,, vol. 6, no. 14. pp. 1–348, 2016.

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Design Methodology

Kroes, P. "Design methodology and the nature of technical artefacts." Design studies 23.3 (2002): 287-302.

Horvath, I., 2004. A treatise on order in engineering design research. Research in Engineering Design, 15(3), pp. 155-181.

Nourian, P. 2016, Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,, vol. 6, no. 14. pp. 1–348, 2016.

“the logical leap in design”an abstract function a concrete form

“This is an important distinction: not every design technology can be regarded as a design methodology.

Many design tools can be used in various situations without enforcing or suggesting a particular way of

designing, i.e. a method for avoiding “the logical leap in design” (Kroes, 2002)” (Nourian, 2016)

“The term methodology refers to ‘a structured collection of methods’, in the same way that the

term technology means ‘a structured collection of techniques’. What distinguishes a research

methodology from a mere collection of methods is a set of theoretical underpinnings, which

can be considered as ‘the theory of the methods’ (Horvath, 2004).”(Nourian, 2016)

34

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Design Methodology

Feedforward Generative Design

“This is an important distinction: not every design technology can be regarded as a design methodology.

Many design tools can be used in various situations without enforcing or suggesting a particular way of

designing, i.e. a method for avoiding “the logical leap in design” (Kroes, 2002)” (Nourian, 2016)

an abstract function a concrete form

“The term methodology refers to ‘a structured collection of methods’, in the same way that the

term technology means ‘a structured collection of techniques’. What distinguishes a research

methodology from a mere collection of methods is a set of theoretical underpinnings, which

can be considered as ‘the theory of the methods’ (Horvath, 2004).”(Nourian, 2016)

Kroes, P. "Design methodology and the nature of technical artefacts." Design studies 23.3 (2002): 287-302.

Nourian, P. 2016, Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,, vol. 6, no. 14. pp. 1–348, 2016.

35

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Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

The Sciences of the Natural The Sciences of the Artificial

Physical Sciences and Life Sciences (Physics, Chemistry, Biology,

etcetera)

Design Sciences, Engineering [Optimization], and Operations

Research (Planning, Scheduling, Management)

concerned with the description, prediction, and understanding

of natural phenomena, based on empirical

evidence from observation and experimentation

concerned with reasoning, envisioning, and devising artificial

systems based on given design requirements or optimization

objectives

Questions Problems

Theories as proven Hypotheses Methods as approved Propositions

Explanation and Justification Transformation and Reasoning

Deterministic Models, Stochastic Models Configured Systems, Reconfigurable Systems

Mathematical and/or Computational

Modelling, Analysis, & Simulation

Mathematical and/or Computational

Problem Formulation & Problem Solving

How do things change? How to change things?

MATHEMATICS

“mathematics is the queen of sciences, [and the main driving force behind scientific discovery]”

Carl Friedrich Gauss, [additions from Marcus du Sautoy]

Mathematics is not exactly a branch of science but rather the universal language of sciences.

It does not concern itself with concrete matters but with abstract patterns behind them.

More Information: https://en.wikipedia.org/wiki/The_Sciences_of_the_Artificial

Definitions

Generative Design Research ≔The Sciences of the Artificial

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Causal Systems vs. Conscious Beings

https://en.wikipedia.org/wiki/Anticipatory_Systems;_Philosophical,_Mathematical,_and_Methodological_Foundations

https://www.springer.com/gp/book/9781461412687

There is no reason for water boiling, there is

a cause for it. Water does not decide to boil,

it just boils, for a cause, prior to the effect.

The boss is angry for a reason (a valid reason?). The

boss decides what to do next, based on an anticipation

of future, posterior to the action.

The behaviour of causal systems is inherently predictable, whereas the behaviour of conscious beings seems to be [is?]

unpredictable.

37

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About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

The Scientific Method

“A method of procedure that has characterized natural sciences since the 17th century,

consisting in systematic observation, measurement, and experiment, and the formulation, testing,

and modification of hypotheses.”

‘criticism [scepticism] is the backbone of the scientific method’

from Oxford Dictionary

Also known as:

Mathematical Modelling

And since ~1970’s also as:

Computational Modelling/Simulation

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The Scientific Method

Modelling

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Epistemology

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Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

The Scientific Method≠Statistcis

Hypothesis

Testing

Data Analysis

Observation

Question

Mathematical

Modelling

Computational

[Simulation] Modelling

“A method of procedure that has characterized natural sciences since the 17th century,

consisting in systematic observation, measurement, and experiment, and the formulation, testing,

and modification of hypotheses.”

‘criticism [scepticism] is the backbone of the scientific method’

from Oxford Dictionary

Also known as:

Mathematical Modelling

And since ~1970’s also as:

Computational Modelling/Simulation

39

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Methodology

D/R Methodology

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

What is a model?

Physical Model

Statistical Model

Phillip's Economic Computer

Mathematical

Model

𝑇𝑖,𝑗 = 𝐺 𝑚𝑖𝑚𝑗

𝐷𝑖,𝑗

2

Gravity Model of Trade

A Markov Chain Model

of the Stock Market

Computational Model

𝒙(𝑡+1) = 𝑷𝒙(𝑡)

Fitting a Linear Model to Data Points

A simplified replica of a system that is capable of partially mimicking the behaviour of the system.

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Modelling

Complexity

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Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Why model?

We make a model to perceive/grasp/understand a phenomenon or a system.

Structure/Mechanism: A good/useful model not only helps predict some output of a system

but also helps us understand and explain the structures/mechanisms sophisticating the

behaviour of a system/phenomenon.

Dynamics: We often make models to study how a change in the conditions results in a change

in the behaviour of a system. We model systems and phenomena in terms of variable inputs

and dynamic outputs.

Didactics: The process of learning or grasping something can be deemed as a process of

evolving mental models, from overly simplistic ones to more sophisticated ones.

A simplified replica of a system that is capable of partially mimicking the behaviour of the system.

Epstein, Joshua M. "Why model?." Journal of Artificial Societies and Social Simulation 11.4 (2008): 12. 41

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Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Professor Butts and the Self-Operating Napkin (1931), a cartoon by Rube Goldberg

Image Credit: https://en.wikipedia.org/wiki/Rube_Goldberg_machine A Facebook® creation designed for making life more or less complicated

COMPLEX vs COMPLICATED

Complexity

complex≠complicated

Complicated is that which is difficult to grasp or deal with.

Complex is that which is sophisticated in that it [spatially] consists of many parts interrelated to one another, [temporally] demonstrates circular causality

because of feedback loops, and/or combinations of both sophistications resulting in emergent patterns and/or chaotic behaviour.

Complexity Sciences study real-world complex phenomena by making simplified mathematical/computational replicas. 42

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The Scientific Method

Modelling

Complexity

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Generative Design

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Mathematical Derivation

Gamified Exploration

References

Collective Intelligence: Complexity & Emergence

https://en.wikipedia.org/wiki/Emergence

Organization and Structure

Emerging out of Collective

Behaviour

The whole being greater than the

sum of parts, having [smart]

properties arising from interactions

of the [not-necessarily smart] parts.

Irreducibility: the system can only

be understood by looking at the

interactions of the parts. The system

cannot be reduced to [some of] its

constituent elements.

A Termites' Cathedral manifesting the genesis of a magnificent masonry architecture through collective

intelligence, Photographed by Fiona Stewart in Queensland, featured by Prof. Richard Dawkins,

Comparison with Sagrada Familia of Antoni Gaudi by the Philosopher Daniel Dennett in his book From

Bacteria to Bach and Back: The Evolution of Minds. Prof. Richard Dawkins: No architect (as Dan Dennett

pointed out) no blueprint, not even in DNA. They just followed local rules of thumb, like cells in an

embryo. ref

More Information: https://genesis-lab.dev/courses/earthy/ 43

Motivation

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Collective Intelligence: Complexity & Emergence

Organization and Structure Emerging out of Collective Behaviour

The whole being greater than the sum of parts, having [smart] properties arising from interactions of

the [not-necessarily smart] parts. Irreducibility: the system can only be understood by looking at the

interactions of the parts. The system cannot be reduced to [some of] its constituent elements.

A slime mold network foraging network replicating the design of the metropolitan rail network of metropolitan area of Tokyo. The genesis of a highly sophisticated network

through collective intelligence is a source of inspiration for Generative Design of Architectural Configurations by devising Multi-Agent Systems in the course Spatial Computing

Design Studio. Image from AAAS/Science

More Information: https://genesis-lab.dev/courses/spatialcomputing/ 44

Motivation

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Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Leading AI textbooks define the field as the study of "intelligent agents": any device that

perceives its environment and takes actions that maximize its chance of successfully achieving

its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or

computers) that mimic "cognitive" functions that humans associate with the human mind, such

as "learning" and "problem solving".[4]

Artificial Intelligence=

“Machine’s ability to discern, map, and decide in face of complexity and uncertainty”

1. Definition of AI as the study of intelligent agents: Poole, Mackworth & Goebel (1998), which provides the version that is used in this article.

These authors use the term "computational intelligence" as a synonym for artificial intelligence.[1]

2.Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field".[2]

3.Nilsson 1998

4.Legg & Hutter 2007

5.Russell & Norvig 2009, p. 2.

Explainable AI (XAI)=“methods and techniques in the application of artificial

intelligence technology (AI) such that the results of the solution can be understood by humans”

(https://en.wikipedia.org/wiki/Explainable_artificial_intelligence)

Machine Learning, Machine Vision, Fuzzy Logics, Multi-Agent Systems, Meta-Heuristics,

etcetera.

“Post-Modern Mathematics”

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Epistemology

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Mathematical Derivation

Gamified Exploration

References

Definitions

There are two major dimensions along which research methodologies differ with respect to

their underlying approaches, epistemological principles, and praxis: rationalism-empiricism

and atomism-holism. The distinctions are made to help with navigation, the world of research

methods is more connected than what may appear in this image.

Research Methodology

https://science-network.tv/philosophy-of-science/ 46

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Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

There are two major dimensions along which research methodologies differ with respect to

their underlying approaches, epistemological principles, and praxis: rationalism-empiricism

and atomism-holism. The distinctions are made to help with navigation, the world of research

methods is more connected than what may appear in this image.

Research Methodology

https://science-network.tv/philosophy-of-science/

Generative Design

Research Methodology

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Generative Design

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Mathematical Derivation

Gamified Exploration

References

Definitions

Research Methodology

Objectivity Inter-Subjectivity Subjectivity

Context of Justification Context of Interpretation Context of Discovery

Anybody and Everybody The Community The Individual

The Universal Realm The Social Realm The Private Realm

Facts Social Constructs Opinions

Repeatable Experiment Social Consensus Personal Experience

Complexity Sciences

The Spectrum of Epistemology

•Okasha, S., 2002. Philosophy of Science: A Very Short Introduction. s.l.: Oxford University Press, USA.

•Fallman, D., 2003. Design-oriented Human—Computer Interaction. s.l., ACM, pp. 225-232.

•Dorst, K., 2007. The Problem of the Design Problem. In: Expertise in Design - Design Thinking Research Symposium 6. Sydney: Creativity and Cognition Studios Press.

“Not everything that counts can be counted, and not everything that can be counted counts.”

(William Bruce Cameron)

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The Scientific Method

Modelling

Complexity

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Epistemology

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Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Logic (from Greek: λόγος (lógos,“speech, reason”) or λογική,logikḗ,

'possessed of reason,intellectual,dialectical,argumentative')[1][2][i] is the systematic study of valid rules of inference, i.e.

the relations that lead to the acceptance of one proposition (the conclusion) on the basis of a set of other propositions

(premises).

Definitions

Method: from Greek words μετά+οδος or μέθοδος, that can be translated to ‘way of ways’.

“A particular procedure for accomplishing or approaching something, especially a systematic or established one.”

Oxford Dictionary

The Scientific Method is a meta-level term to describe research methods that can derive objectively

verifiable and reproducible knowledge, while ensuring rigorous scepticism and rejecting bias.

Research Methodology

Praxis

praxis, noun /ˈpræksɪs/ [uncountable] (philosophy)

a way of doing something; the use of a theory or a belief in a practical way

“Analysis, Synthesis, and Evaluation by means of Logical Reasoning, refuting Logical Fallacies”

λόγος≃“The art (grammar) and the science (mathematical logic) of reasoning”⊂Trivium

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Methodology

D/R Methodology

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Definitions

Research Methodology

Generative Design Praxis

praxis, noun /ˈpræksɪs/ [uncountable] (philosophy)

a way of doing something; the use of a theory or a belief in a practical way

Linguistics: Generative Grammars (Grammatical/Syntactic Exploration or Itemization),

Partial Differential Equations: Mathematical Optimization (Mathematical/Physical Deduction or Derivation)

Graph Theory + Game Theory: Serious Gaming for systematic Negotiation and Consensus Building

λόγος (lógos,“speech, reason”)

Analysis, Synthesis, and Evaluation by means of Logical Reasoning, refuting Logical Fallacies

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D/R Methodology

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

https://elrincondeniko.wordpress.com/2016/08/21/linguistics-for-dummies-transformational-generative-grammar-i/

(Grammatical/Syntactic Exploration or Itemization)

Image credit: https://en.ppt-online.org/286759

Noam Chomsky, Photo credit: Jimi Giannatti

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The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 52

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 53

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 54

Motivation

Introduction

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Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 55

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 56

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 57

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 58

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 59

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 60

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 61

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 62

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 63

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 64

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 65

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 66

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Linguistics: Generative Grammars

(Grammatical/Syntactic Exploration or Itemization)

Image Credit: Tarang Gupta, Divyaye Mittal, Prateek Wahi, Andrea Fumagalli, Filip Zielinski, Aditya Parulekar, EARTHY 2019 67

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematics: Topology Optimization

(Mathematical Derivation of form from Physical Laws [Partial Differential Equations])

Image Credit: Ir. Rick van Dijk, Graduation thesis project, https://genesis-lab.dev/graduation/ 68

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematics: Topology Optimization

(Mathematical Derivation of form from Physical Laws [Partial Differential Equations])

Image Credit: Ir. Rick van Dijk, Graduation thesis project, https://genesis-lab.dev/graduation/ 69

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematics: Topology Optimization

(Mathematical Derivation of form from Physical Laws [Partial Differential Equations])

Image Credit: Ir. Rick van Dijk, Graduation thesis project, https://genesis-lab.dev/graduation/ 70

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematics: Topology Optimization

(Mathematical Derivation of form from Physical Laws [Partial Differential Equations])

Image Credit: Ir. Rick van Dijk, Graduation thesis project, https://genesis-lab.dev/graduation/ 71

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Project TerraTetris, Aditya Pravin Soman, Vicente Blanes, Christina Koukelli, Neha Gupta, and Dion van Vlarken, Earthy 3.0

Spatial Decision Making, (EquiCity Game, 2021)

72

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Project TerraTetris, Aditya Pravin Soman, Vicente Blanes, Christina Koukelli, Neha Gupta, and Dion van Vlarken, Earthy 3.0 73

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Project TerraTetris, Aditya Pravin Soman, Vicente Blanes, Christina Koukelli, Neha Gupta, and Dion van Vlarken, Earthy 3.0 74

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Alessandro Passoni, Alessio Rigorito, Kiana Mousavi, Fredy Fortich Mora, Stephanie Moumdjian, EARTHY 2.0 75

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Alessandro Passoni, Alessio Rigorito, Kiana Mousavi, Fredy Fortich Mora, Stephanie Moumdjian, EARTHY 2.0 76

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Alessandro Passoni, Alessio Rigorito, Kiana Mousavi, Fredy Fortich Mora, Stephanie Moumdjian, EARTHY 2.0 77

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Alessandro Passoni, Alessio Rigorito, Kiana Mousavi, Fredy Fortich Mora, Stephanie Moumdjian, EARTHY 2.0 78

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Alessandro Passoni, Alessio Rigorito, Kiana Mousavi, Fredy Fortich Mora, Stephanie Moumdjian, EARTHY 2.0 79

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Games: Linguistics & Mathematics

Systematic Rule-Based/Syntactic Exploration

Image Credit: Anne Leltz, student work in BK3OV3, an example of Topological Design via the Walk-Stand-Sit Method, 2017-2018, tutor, Pirouz Nourian

Compose a Program of Requirements (PoR):

●A list of Functional Spaces and their sizes and

desirable proportions and free-heights.

●A matrix of relations among these spaces, as a Activity

Relations Chart (ARC)

Define three layers of spaces for walking, standing, and sitting

For every functional space (where people are to sit) make a

sized and proportioned rectangle.

Make modularized ramps, stairs and corridor pieces.

Connect the functional (sitting space) rectangles using ramps,

stairs, and corridors.

Consider a bounding box smaller than or equal to the available

volume and fit all functional spaces + connections inside the

bounding box considering their free heights. This will be the

spatial configuration.

You can morph the spatial configuration topologically to fit to

the desired shape.

Walk-Stand-Sit: The 7 Golden Game Rules

80

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematical Design Games

Image Credits: Maximillian Michl, Course Name, Spatial Computing

Noise Analysis

Connectivity

Sunlight Analysis 81

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematical Design Games

Image Credits: Maximillian Michl, Course Name, Spatial Computing

Massing Synthesis

Pathways & Space Seeds

Configuration=Massing & Circulation 82

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Mathematical Design Games

Image Credits: Maximillian Michl, Course Name, Spatial Computing 83

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

84

MSc3, BT, AR3B011

Generative Design Methodology Projects

Decision Making Panel, (EquiCity Game, 2021)

Profile Panel, (EquiCity Game, 2021)Game Information Panel, (EquiCity Game, 2021)

Mathematical Game Engine Flowchart,

Pirouz Nourian & Shervin Azadi (EquiCity

Game, 2021)

Decision Making Panel, (EquiCity Game, 2021)

Profile Panel, (EquiCity Game,

2021)

Game Information Panel,

(EquiCity Game, 2021)

Decision Making Panel,

(EquiCity Game, 2021)

problem

dimensions

constraints

mathematical

methods

.allocation of discrete spatial units to different functions

.actors, sites, functions (colors)

.different assignment of colors to sites

.required area per color for the district

.limited area per site

.Online Interactive Interface (Multi-Actor)

.Opinion Pooling (Multi-Actor)

.Proportional Fitting (Multi-Actor)

.Weighted Massing (Multi-Dimensional)

.Spatial Performance Evaluation (Multi-Dimensional)

.Multi Criteria Decision Analysis (Multi-Criteria)

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

MSc3, BT, AR3B011

Generative Design Methodology Projects

Decision Making Panel, (EquiCity Game, 2021)

Profile Panel, (EquiCity Game, 2021)Game Information Panel, (EquiCity Game, 2021)

Decision Making Panel, (EquiCity Game, 2021)

Profile Panel, (EquiCity Game,

2021)

Game Information Panel,

(EquiCity Game, 2021)

Decision Making Panel,

(EquiCity Game, 2021)

.educational context (MSc and BSc)

.research context (EquiCity)

.topoGenesis (python library)

.supporting variety of methodologies from optimization to

gamification

.supporting variety of spatial quality criteria

.compatible with both modular and integral construction

techniques

.hard to reach specific solution because of the decision

priority

.formulation of spatial quality criteria

.benchmarking with standardized problems and methods

.connections with Reinforcement learning

application

implementation

generality

limitations

future works

Image Credits: Hugo van Rossum, Maren Hengelmolen. Liva Sadovska, Sander Bentvelsen, Spatial Computing Design Studio 3.0 85

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Generative Design:

•Spatial Mathematics (Linear Algebra, Computational Geometry, Topology, Graph Theory)

•Fundamentals of Computer Science

•Algorithm Design and Programming (Python, C#)

•Gamification of Design

•Modular & Combinatorial Design

Minor BK-MI-197

MSc3, BT, AR3B011

https://genesis-lab.dev/courses/spatialcomputing/ https://genesis-lab.dev/courses/earthy/

Generative Design Courses

86

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Image from: https://genesis-lab.dev/about/

Generative Design Tools

87

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

More info: https://genesis-lab.dev

Acknowledgements

88

Dr.ir. Matthijs Langelaar,

Associate Professor of

Structural Optimization and Mechanics

Scientific Advisor of Genesis Lab

Prof.dr. E. Eisemann,

Professor of

Computer Graphics & Visualization

Scientific Advisor of Genesis Lab

Ir. Shervin Azadi

Researcher and Instructor of

Design Informatics

Technological Director of Genesis Lab

Dr. Tom van Mele,

Co-director of Block Research Group

Computational Design & Engineering

Scientific Advisor of Genesis Lab

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Read more:

about Agent-Based Models, Cellular Automata and Markov Chains

and their use in modelling spatial and temporal dynamics of social phenomena

here.

Further reading:

[1] J. M. Epstein, “Why Model?,” J. Artif. Soc. Soc. Simul., vol. 11, no. 4, p. 12, 2008.

[2] T. Schelling, Micromotives and Macrobehavior. 2006.

[3] A. J. Heppenstall, A. T. Crooks, L. M. See, and M. Batty, Eds., Agent-based models of geographical systems, Heppenstal. Dordrecht: Springer, 2012.

[4] S. P. Borgatti and P. C. Foster, “The network paradigm in organizational research: A review and typology,” Journal of Management, vol. 29, no. 6. pp. 991–1013, 2003.

[5] P. Nourian, “Configraphics: Graph Theoretical Methods for Design and Analysis of Spatial Configurations,” Doi.Org, vol. 6, no. 14. pp. 1–348, 2016.

[6] G. P. Richardson, “System Dynamics,” in Encyclopaedia of Operations Research and Management Science, Boston, MA: Springer US, 2013, pp. 1519–1522.

[7] R. Oval, Topology Finding of Patterns for Structural Design, Universite Paris Est, PhD dissertation

[8] N. Bai, S. Azadi, P. Nourian, A. Pereira Roders, Decision-Making as a Social Choice Game: Gamifying an urban redevelopment process in search for consensus,

eCAADe2020 –Anthropologic, TU Berlin, Germany, Volume: 2

[9] P. Nourian, How to write a thesis? A Generative Design Graduate Studio Guidebook. (2019). Delft University of Technology, Faculty of Architecture and Built

Environment, Department of Architectural Engineering and Technology. DOI: 10.6084/m9.figshare.11987328

[10] P. Nourian, S. Azadi, and F. van Andel, “Open Source Participatory Design and Construction of Open Buildings: Affordable ‘Haute Couture’ for the Masses by means

of Design-Build Games:,” presented at the Open Building Now! 2.0, Mar. 16, 2021. doi: 10.13140/RG.2.2.30315.46888. [URL]

[11] P. Nourian, Generative Design Research Methodology: Theoretical underpinnings of practice for systematic deduction and exploration in design. 2020. doi:

10.13140/RG.2.2.30096.84484. [URL]

[12] S. Azadi and P. Nourian, “Collective Intelligence in Generative Design: A Human-Centric Approach Towards Scientific Design,” BouT: Periodical for the Building

Technologist, vol. Generative Design, no. 76, pp. 7–16, Apr. 2021. doi: 10.13140/RG.2.2.15295.84642. [URL]

[13] S. Azadi and P. Nourian “GoDesign - A modular generative design framework for mass-customization and optimization in architectural design,” 2021. Accessed: Aug.

16, 2021. [Online]. Available: http://papers.cumincad.org/cgi-bin/works/paper/ecaade2021_263 [URL]

[14] P. Nourian, S. Azadi, H. Hoogenboom, S. Sariyildiz, Earthy: Generative Design for Earth and Masonry Architecture, DOI: 10.13140/RG.2.2.28390.65607, [URL]

Further Reading

89

Motivation

Introduction

Relevance

Design Paradigms

Design Research

Methodology

D/R Methodology

About Science

The Scientific Method

Modelling

Complexity

Research Compass

Epistemology

Praxis

Generative Design

Grammatical Itemization

Mathematical Derivation

Gamified Exploration

References

Video Presentation

Questions:

p.nourian[]tudelft.nl

90