Emergent Design

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Emergent Design
Martin Hemberg Imperial College 2004 Emergent
Design
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Who's that guy and what's he doing up there?

• Martin Hemberg
• Developed Genr8 with the Emergent Design Group
  (EDG)
• Work at Emergent Design Technologies (EmTech)
  Architectural Association (AA)

Martin Hemberg Imperial College 2004 Emergent
Design
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Agenda

• Motivation
• Evolutionary Computation (EC)
• Artificial Life (Alife)
• EC and Alife combine well for design tasks
• Example applications

Martin Hemberg Imperial College 2004 Emergent
Design
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Motivation, Architecture

• Break new grounds in architecture
• ED uses a different logic
• Natural form has aesthetic and functional values
• Hard to obtain using ordinary methods

Martin Hemberg Imperial College 2004 Emergent
Design
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Motivation, Computer Science

• Application of EC
• Exploration, not optimisation
• Fitness evaluation
• Use computers creatively
• Beyond CAD-tools
• Requires new algorithms

Martin Hemberg Imperial College 2004 Emergent
Design
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Evolutionary Computation

• Optimisation method
• Randomized
• Inspired by natural evolution
• Population adaption generation by generation
• Comes in many flavours GA, GP, ES, GE, etc

Martin Hemberg Imperial College 2004 Emergent
Design
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Neo Darwinian Evolution

• Survival of the fittest
• Selection on phenotype
• Through environment
• Genotypic inheritance
• Reproduction
• Blind variation

Martin Hemberg Imperial College 2004 Emergent
Design
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Artificial Evolution

• Pseudocode for an EA
• generation 0initialize populationwhile
  generation lt max-generation evaluate fitness of
  population members for i from 1 to
  population-size select two parents crossover
  parents -gt child mutate child insert child
  into next generations population endfor gener
  ation update current populationendwhile

Martin Hemberg Imperial College 2004 Emergent
Design
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Selection

• Selection ensures that fitter individuals have a
  higher probability of being selected for the next
  generation
• Tournament
• Proportional

Martin Hemberg Imperial College 2004 Emergent
Design
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Fitness

• A leap from natural evolution
• A quantified numerical value is assigned to each
  member
• Try each member on the problem and rank them or
  quantify their performance

Martin Hemberg Imperial College 2004 Emergent
Design
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Fitness Evaluation

• How to assign fitness according to aesthetic
  criteria?
• EA are good at finding optimal solutions
• Need to figure out what to optimize
• Open problem

Martin Hemberg Imperial College 2004 Emergent
Design
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Fitness Evaluation, strategies

• Rule based
• Hard to define and encode rules
• Learn user preference with neural network
• Too many parameters, fails in practice
• User acts as fitness function
• Human fatigue, short runs
• Co-evolve critics

Martin Hemberg Imperial College 2004 Emergent
Design
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Fitness Evaluation, my view

• Put the user in the loop
• Create tools with the designer in mind
• Make them open-ended
• Can't predict user's need and context
• Parameterized fitness function
• User has high level control of evaluation
• Fitness emerges as a combination of factors

Martin Hemberg Imperial College 2004 Emergent
Design
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What is Artificial Life

• How does life arise from the non-living?
• What are the potentials and limits of living
  systems?
• How is life related to mind, machines, and
  culture?

Martin Hemberg Imperial College 2004 Emergent
Design
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Two definitions of emergence

• The whole is greater than the sum of the parts
• Emergence is the phenomenon wherein complex,
  interesting high-level function is produced as a
  result of combining simple low-level mechanisms
  in simple ways.
• Examples include brain, society

Martin Hemberg Imperial College 2004 Emergent
Design
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Alife and EC for Design

• Evolutionary computation
• Creative and generative qualities
• Discovery and adaptation more than optimization
• ALife
• Agents interacting with environment can model
  elements of design and conditions of the problem
• Emergent properties in outcome from bottom-up
  approach

Martin Hemberg Imperial College 2004 Emergent
Design
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Surface Component System

• Simple growth model
• Select tiles from a predefined set
• Rules for which tiles are allowed
• Incorporates structural analysis in the EA

Martin Hemberg Imperial College 2004 Emergent
Design
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Using the tool

• Implemented as a MEL script
• FEA inAnsys

Martin Hemberg Imperial College 2004 Emergent
Design
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Geometric Fitness criteria

• Fast and easy to evaluate and understand
• Number of support points
• Support point distance
• Height
• Holes

Martin Hemberg Imperial College 2004 Emergent
Design
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Structural Fitness criteria

• FEA is computationally costly
• Don't evaluate each generation

Martin Hemberg Imperial College 2004 Emergent
Design
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Genr8 A Design Tool for Surface Generation

• Combines EC and an organic growth model
• Surface are grown in a reactive simulated
  physical environment

Martin Hemberg Imperial College 2004 Emergent
Design
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Lindenmayer Systems

• Organic growth model
• Widely applied to model plant growth in computer
  graphics
• L-systems are important in formal language theory

Martin Hemberg Imperial College 2004 Emergent
Design
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Rewriting systems

• A set of production rules are repeatedly applied
  to a seed
• Rules are expressed as a grammarSeed aRule a
  -gtab b-gtba

Martin Hemberg Imperial College 2004 Emergent
Design
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Turtle Graphics

• Turtle graphics is a way to visualize the grammar
• Rules are interpreted as instructions for moving
  and drawing in 3D spaceSeed aRule a-gtaa--a
  aAngle 60

Martin Hemberg Imperial College 2004 Emergent
Design
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Plant Models

• Operators (push state on stack) and (pop
  state from stack) allows branching
• Time delay
• Stochasticity
• Environmen (tropism)Seed aRule a-gtaaaAng
  le 45

Martin Hemberg Imperial College 2004 Emergent
Design
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Map L-Systems
b -gt b
b
b
Martin Hemberg Imperial College 2004 Emergent
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HEMLS

• 3D
• Scaling
• More complex productions
• Context sensitivity
• Time variation
• Stochastic

Martin Hemberg Imperial College 2004 Emergent
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Environment

• Forces
• Attractors
• Repellors
• Gravity
• Boundary

Martin Hemberg Imperial College 2004 Emergent
Design
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Evolution

• Search the universe of possible surfaces
• Find a grammar corresponding to the surface that
  the designer has in mind
• Explore the universe to find interesting forms

Martin Hemberg Imperial College 2004 Emergent
Design
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Grammatical Evolution

• Automatic generation of grammars
• Very hard to construct by hand
• Many constraints -gt problematic for GP
• Grammatical Evolution allows any language
• Use Backus-Naur Form (BNF) to map linear genome
  into a grammar
• Genetic operations are separated from language

Martin Hemberg Imperial College 2004 Emergent
Design
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Mappings

• Genr8 contains several mappings
• Increases the complexity
• Individuals represented by linear genome
• Selection on the phenotype that is expressed
  through an environment

Martin Hemberg Imperial College 2004 Emergent
Design
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Design Evaluation and Fitness

• Fitness function with multiple parameters
• Size
• Smoothness
• Soft boundary
• Subdivisions
• Symmetry
• Undulation

Martin Hemberg Imperial College 2004 Emergent
Design
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Fitness Criteria

• User determines target values and weight for the
  criteria
• Multiparameter optimization
• Trade-off between criteria
• Population gives a family of solutions

Martin Hemberg Imperial College 2004 Emergent
Design
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Interruption, Intervention and Resumption (IIR)

• Traditionally, EA are monolithic
• User can guide the evolution by interacting and
  interfering
• Allows for greater control
• The tool cooperates with the user

Martin Hemberg Imperial College 2004 Emergent
Design
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Using Genr8

• Set up environment
• Define fitness criteria and other parameters
• Run a few generations
• Analyze the results, adjust parameters and
  environment

Martin Hemberg Imperial College 2004 Emergent
Design
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More on Emergent Design

• Genr8 websitehttp//www.ai.mit.edu/projects/emerg
  entDesign/genr8/
• EDG websitehttp//web.mit.edu/arch/edg/
• EmTech website
• http//www.aaschool.ac.uk/et

Martin Hemberg Imperial College 2004 Emergent
Design