We continue by telling people that they can look into the history and learn more about the cartograph. History
Governing FeaturesMaybe a single sentence on the principles with a link to its page. Governing Feature
Urbanism Through the Lens of Complexitywe continue with the shortest intro to the urban fields. Urbanism
Quickly dive into complexity theory and how it can work with urbanism fields through search.
Relates to {{Assemblage-Geography}}
All points are interconnected and interdependent, unfolding in a nonlinear manner with no central source of authority.
Early versions of systems theory assumed that systems could be 'optimized' to a single condition. CAS analysis assumes that more than one system state can satisfy optimizing criteria, and so the system is able to gravitate to multiple equilibria.
This is relevant to the field of Relational Geography
An enslaved state can persist as an attractor (see Attractor States) within a Fitness Landscape.
Beyond its day-to-day usage, this term used in now employed in the social sciences to highlight the Path Dependency exhibited in many social systems. This is seen to contrast with prior conceptions like "the march of history", which imply a clear causal structure. By speaking about the work as something contingent, it also begs the question of what other "worlds" might have just as equally manifested, had things been slightly different.
Similar ideas are captured in the ideas of Non-Linearity, {{sensitivity-to-initial-conditions}}, History Matters.
Pictured below: the contingent trajectory of the double pendulum:
See also: Causal loop diagram - Wikipedia
In geography there has been a move away from thinking about space as a "thing" and to instead think about how different places exist due to how they interact with flows. Places that capture more flows, are more geographically relevant
The nature of a building block varies according to the system: it may take the form of an ant, a cell, a neuron or a building.
Complex Adaptive Systems theory provides a useful lens with which to understand various phenomena. Keep reading about Complexity
Well this is some nice and text to help us with whatever this should be. Keep reading about Urbanism
Urban FieldsWe continue by telling people that they can look into the history and learn more about the cartograph. People
TermsMaybe a single sentence on the principles with a link to its page. Terms
Navigating Complexity brings in a wealth of resources and related content associated to the topics and terms. You can see all of them sorted by type.
The site features a system for the submission and evaluation of explanatory diagrams relating to a variety of CAS topics.
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Navigating Complexity is a platform for learning about complex adaptive systems and how they apply to the built environment.
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Explore an array of key concepts related to complexity! Each concept is defined using non-mathematical descriptions with reference to key thinkers, publications, and associated terms.
The Concepts below are ones frequently discussed in relation to complexity theory. They can be considered individually or - by using the Navigating Complexity feature - they can be understood in relation to the governing features or urban fields they are associated with. The decision of what qualities should be described here as "Core" vs those aspects that appear in "Terms" is not precise: many core features of complex systems are described using more than one descriptive term. Accordingly, the concepts chosen here are intended to provide an overview of central dynamics - which may be also be captured using other terms: as much as possible when the same concept is referred to using different terms, the description will point to these alternative descriptors (found in terms).
A tipping point (often referred to as a 'critical point') is a threshold within a system where the system shifts from manifesting one set of qualities to another.
CAS tend to organize to a 'critical state' where, regardless of the scale of a given input, the scale of corresponding output observes of a power-law distribution.
Self-organization refers to processes whereby coordinated patterns or behaviors manifest in a system without the need for top-down control.
'Scale-free' networks are ones in which identical system structure is observed for any level of network magnification.
Complex systems are composed of agents governed by simple input/output rules that determine their behaviors.
Complex System behaviors often exhibit power-laws: with a small number of system features wielding a large amount of system impact.
'Path-dependent' systems are ones where the system's history matters - the present state is contingent upon random factors that governed system unfolding, and that could have easily resulted in other viable trajectories.
Open & dissipative systems, while 'bounded' by internal dynamics, nonetheless exchange energy with their external environment.
Network theory allows us think about how the dynamics of agent interactions in a complex system can affect the performance of that system.
CAS systems unfold over time, with agents continuously adjusting behaviors in response to feedback. Each iteration moves the system towards more coordinated, complex behaviors.
What drives complexity? The answer involves a kind of sorting of the differences the system must navigate. These differences can be understood as flows of energy or information.
Complex Adaptive Systems become more 'fit' over time. Depending on the system, Fitness can take many forms, but all involve states that achieve more while expending less energy.
Feedback loops occur in system where an environmental input guides system behavior, but the system behavior (the output), in turn alters the environmental context.
Left to themselves, systems tend towards regimes that become increasingly homogenous or neutral: complex systems differ - channeling continuous energy flows, gaining structure, and thereby operating far from equilibrium.
'Degrees of freedom' is the way to describe the potential range of behaviors available within a given system. Without some freedom for a system to change its state, no complex adaptation can occur.
Cybernetics is the study of systems that self-regulate: Adjusting their own performance to keep aligned with a pre-determined outcome, using processes of negative-feedback to help self-correct.
Complex Systems can unfold in multiple trajectories. However, there may be trajectories that are more stable or 'fit'. Such states are considered 'attractor states'.
Photo Credit and Caption: Credit: Matthew Rader via Unspash
Cite this page:
Wohl, S. (2022, 3 June). Core Concepts. Retrieved from https://kapalicarsi.wittmeyer.io/taxonomy/key-concepts
Core Concepts was updated June 3rd, 2022.
Related Key Concepts
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Related Governing Features
This is a list of Governing Features that Core Concepts is related to.
Related Urban Fields
This is a list of Urban Fields that Core Concepts is related to.
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