An Evolutionary Approach to Design Collaboration
cgen.dlang
is a collaborative design system developed for small communities (5 – 50 people) who want to generate a collection of the team created and computer mutated visual structures that are likely to be optimal reflections of a team’s aesthetic values. These visual structures capture the full transmission history of aesthetics and are used to form design language systems.
cgen.dlang’s
infrastructure relies on a cocktail of programming languages for front-end and back-end specification and implementation.
cgen.dlang’s
system architecture. Users interface with the cgen.dlang
interface to design structures
(seed design) that are functions of the underlying component library
and associated grammar
. Users also have the option of voting()
on other user-generated structures and genetically generated structures.
The structure (system architecture) of cgen.dlang
is composed of the following components: component library, component grammars, voting models, and evolutionary processes.
-
component library - collection of pre-defined
assets
-
component grammars - set of rules that define acceptable
operations
on and betweencomponents
to formstructures
-
voting models -
schema
outlining the method by which breeding candidates are selected -
evolutionary processes
- The
solution space
- A
random population
ofgenotypes
(possible solutions) - Fitness function(s)
- Virtual
variational operators
:compare()
,mutate()
,cross()
- The
# Start here
cd cgen_server
# Install dependencies
pip install -r requirements.txt
# And go...
python server.py
# Congifgure front-end
docker run -p 5432:5432 --name cgendlangpostgres -e POSTGRES_PASSWORD=cgendlangpostgres -d postgres
# Navigate to server and install
cd server
npm install
# Create the database structure
node_modules/knex/bin/cli.js migrate:latest
# Generate the first examples
node make_randoms.js
# Generate a cache of image keys for the front page (do it every time you want to update the front page)
node updatecache.js
# And go...
node server.js
from cgen.dlang import cgen.example
import cgen.dlang as cgen
import ganbreeder as gan
import tensorflow as tf
import pytorch as torch
import numpy as np
# Generate structure
cgen.Gen_STRUCT(cgen.example.components, ..., cgen.example.operations)
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