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Diagram: Variables

Variables

For a system to adapt, it needs to have variables to adjust.

See also: Requisite Variety

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Example of different degrees of freedom represented as slider bars:

We can imagine tuning a system with any number of variables (beyond 3!)

 

Cite this page:

Wohl, S. (2022, 7 June). Variables. Retrieved from https://kapalicarsi.wittmeyer.io/definition/variables

Variables was updated June 7th, 2022.

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Evolution

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Reaction/Diffusion | Computation

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Cellular Automata & Agent-Based Models offer city simulations whose behaviors we learn from. What are the strengths & weaknesses of this mode of engaging urban complexity?

There is a large body of research that employs computational techniques - in particular agent based modeling (ABM) and cellular automata (CA) to understand complex urban dynamics. This strategy looks at how rule based systems yield emergent structures.

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New ways of modeling the physical shape of cities allows us to shape-shift at the touch of a keystroke.  Can this ability to generate a multiplicity of possible future urbanities help make better cities?

Parametric approaches to urban design are based on creating responsive models of urban contexts that are programmed to change form according to how inputs are varied. Rather than the architect creating a final product, they instead create a space of possibilities ({{phase-space}}) that is activated according to how various flow variables - economic, environmental, or social, are tweaked. This architectural form-making approachholds similarities to complex systems in terms of how entities are framed: less as objects in and of themselves, and more as responsive, adaptive agents, activated by differential inputs.
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There would be some thought experiments here.

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Related (this page): Urban Modeling (11), Tactical Urbanism (17), Parametric Urbanism (10), LINKS (56), Requisite Variety (90), Iterations (56), Degrees of Freedom (78), 
Section: terms
Non-Linearity
Related (same section): 
Related (all): Urban Modeling (11, fields), Resilient Urbanism (14, fields), Relational Geography (19, fields), Landscape Urbanism (15, fields), Evolutionary Geography (12, fields), Communicative Planning (18, fields), Assemblage Geography (20, fields), Tipping Points (218, concepts), Path Dependency (93, concepts), Far From Equilibrium (212, concepts), 
Nested Orders
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Related (all): Urban Modeling (11, fields), Urban Informalities (16, fields), Resilient Urbanism (14, fields), Self-Organized Criticality (64, concepts), Scale-Free (217, concepts), Power Laws (66, concepts), 
Emergence
Related (same section): 
Related (all): Urban Modeling (11, fields), Urban Informalities (16, fields), Urban Datascapes (28, fields), Incremental Urbanism (13, fields), Evolutionary Geography (12, fields), Communicative Planning (18, fields), Assemblage Geography (20, fields), Self-Organization (214, concepts), Fitness (59, concepts), Attractor States (72, concepts), 
Driving Flows
Related (same section): 
Related (all): Urban Datascapes (28, fields), Tactical Urbanism (17, fields), Relational Geography (19, fields), Parametric Urbanism (10, fields), Landscape Urbanism (15, fields), Evolutionary Geography (12, fields), Communicative Planning (18, fields), Assemblage Geography (20, fields), Open / Dissipative (84, concepts), Networks (75, concepts), Information (73, concepts), 
Bottom-up Agents
Related (same section): 
Related (all): Urban Modeling (11, fields), Urban Informalities (16, fields), Resilient Urbanism (14, fields), Parametric Urbanism (10, fields), Incremental Urbanism (13, fields), Evolutionary Geography (12, fields), Communicative Planning (18, fields), Rules (213, concepts), Iterations (56, concepts), 
Adaptive Capacity
Related (same section): 
Related (all): Urban Modeling (11, fields), Urban Informalities (16, fields), Tactical Urbanism (17, fields), Parametric Urbanism (10, fields), Landscape Urbanism (15, fields), Incremental Urbanism (13, fields), Evolutionary Geography (12, fields), Feedback (88, concepts), Degrees of Freedom (78, concepts),