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Annotations:
  • 1. Input parameters
  • Discrete value
  • Continuous values
  • Permutation sequences
  • 2. Objective functions
  • 3. Constraint functions
  • Design space model as optimization problem
  • Optimization strategies
  • Deterministic methods — ‘solve’
  • Stochastic methods — ‘search’
  • Direct analysis
  • Gradient descent
  • Exhaustive search
  • Heuristics
  • Stochastic search
  • Metaheuristics

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Annotations:
  • Carpo who are talking about a reemergence of vitalistic and irrational forces in the domain of computational design. He talks, even, about magic, or indeterminacy
  • you design a system of evaluation in the end
  • post-optimization
  • That idea is based on risk mitigation
  • delay design decisions until they can best decide what the impact of those design decisions are
  • Rather than making that kind of grand gesture at the start of the project, they’re able to make it at the end of the projec
  • computational tools enable the architect to decrease the gap
  • The question that I have about that is, if computation is making us more efficient, and if computation is changing the design process in this really profound way, will there be space for anyone who doesn’t know how to do it?
  • coding is something that we really need to know, not in order to be competitive, but to be able to say something in the future within our own discourse
  • We are currently working on a project that aims to create an open source platform for students to upload their codes and tools where you will be able to hack and build upon someone else’s too
  • accepted notion that there is an authorless condition of the architect within computational design
  • The job of the designer isn’t so much to come up with a design, but to discover why the design is needed
  • phenomenology
  • That’s a problem of what you can quantify practically versus what is quantifiable in a theoretical sense. What we can quantify today isn’t necessarily what is quantifiable in the world

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Annotations:
  • designers have the challenge of not only meeting quantitative requirements but also, and more importantly to solve them spatially, i.e. to design those elements and devices that allow the control of light penetration.
  • It is this delicate balance between quantitative performance and geometric variables that calls for an integrated optimisation strategy
  • In order to fully exploit the implicit parallelism described by the Schema Theory and therefore increase the chances to arrive at near optimal solutions, a binary digit coding system has been implemented
  • The genetic algorithm selects a string of bits (chromosome) in accordance to how well they respond to a solution (fitness) and then recombine them to produce new ones (offspring)

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Annotations:
  • content (information) and relationships (organization)
  • Biological algorithms such as fractal generation, cellular automata, and structure-preserving transformations lead to vernacular and traditional architectural and urban forms, which are therefore the genuine product of evolutionary developmen
  • Lecture 1: Recursion and the Fibonacci sequence. Universal  scaling. Biophilia
  • Lecture 2: Geometric Recursion and Fractals. The Sierpinski  gasket. Perforation, bending, and folding. Anti-gravity  anxiety. Architecture of the horizontal
  • Lecture 3: Universal distribution of sizes. Fractal design,  ornament, and biophilia. Sustainable systems
  • Lecture 4: Cellular automata. Sierpinski carpets and  sea-shells. Design in hyperspace and connection to the sacred
  • Lecture 5: Harmony-seeking computations. Architectural  harmony. Alexander's theory of centers. Design as computation.  Computational reducibility
  • Lecture 6: Alexander's 15 Fundamental Properties. Three  laws of architecture
  • Lecture 7: Biologically-inspired computation. Genetic  algorithms. Computation versus memory retrieval. Evolutionary  regression
  • Lecture 8: Emergent systems. Examples from Artificial Life.  Inhuman experiments. Architectural education
  • Lecture 9: Symmetry production. Symmetry breaking.  Classical moldings. Elementary particle symmetries. Binding  energy
  • Lecture 10: Generative codes and their application to  building and urban morphology. Secularization destroys public  space. Spiritual architects. Legalizing codes
  • Lecture 11: Duany-Plater-Zyberk (DPZ) codes. The New  Urbanism. Stephen Mouzon's project. Tall buildings
  • Lecture 12: Implementation of generative codes in design.  Urban plazas. Designing for children. Favelas and social  housing

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    Schwartz, Yair, Rokia Raslan, and Dejan Mumovic. n.d. “Multi-Objective Genetic Algorithms for the Minimisation of the Life Cycle Carbon Footprint and Life Cycle Cost of the Refurbishment of a Residential Complex`s Envelope: A Case Study,” 8.
    Natanian, Jonathan. n.d. “ARCHITECTURE AS A COMPLEX ADAPTIVE SYSTEM.”
    Singh, Vishal, and Ning Gu. 2012. "Towards an integrated generative design framework." Design Studies 33 (2): 185–207. https://doi.org/10.1016/j.destud.2011.06.001.
    Kwiecinski, Krystian, Filipe Santos, Ana de Almeida, Bruno Taborda, and Sara Eloy. n.d. “Wood Mass-Customized Housing,” 10.
    Rakha, Tarek, and Christoph Reinhart. 2012. “GENERATIVE URBAN MODELING: A DESIGN WORK FLOW FOR WALKABILITY-OPTIMIZED CITIES,” 8.
    Chronis, Angelos, Alasdair Turner, and Martha Tsigkari. n.d. “Generative Fluid Dynamics: Integration of Fast Fluid Dynamics and Genetic Algorithms for Wind Loading Optimization of a Free Form Surface,” 8.
    Diego, San. 2013. “Façade Apertures Optimization: Integrating Cross-Ventilation Performance Analysis in Fluid Dynamics Simulation.” San Diego, 8.
    Khodadadi, Anahita. 2018. “Synergy of a Genetic Algorithm and TRIZ in Conceptual Design,” 8.
    Kulcke, Matthias, and Wolfgang E Lorenz. n.d. “Utilizing Gradient Analysis within Interactive Genetic Algorithms,” 6.
    Marin, Philippe, Xavier Marsault, Lazaros Elias Mavromatidis, Renato Saleri, and Florent Torres. n.d. “EC-CO-GEN: AN EVOLUTIONARY SIMULATION ASSISTED DESIGN TOOL FOR ENERGY RATING OF BUILDINGS IN EARLY DESIGN STAGE TO OPTIMIZE THE BUILDING FORM,” 8.

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