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Diagram: Local Interactions

Local Interactions

Agents in a Complex System are guided by neighboring agents - nonetheless leading to global order.

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Cite this page:

Wohl, S. (2021, 8 July). Local Interactions. Retrieved from https://kapalicarsi.wittmeyer.io/definition/local-interactions

Local Interactions was updated July 8th, 2021.

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In Depth: Local Interactions

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This is a list of People that Local Interactions is related to.

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  • This is a list of Terms that Local Interactions is related to.

    Complex Systems are generated from the local interactions of multiple AGENTS. These agents are not actively striving to achieve any form of 'global' structure or pattern, but simply behave in their own self interests. Hence, we describe CAS dynamics as being generated from 'the bottom up' as opposed to 'the top down' as would be the case in traditional hierarchical organizations.

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  • This is a list of Urban Fields that Local Interactions is related to.

    Cellular Automata & Agent-Based Models can provide 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 research looks at rule based systems that 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 that is activated according to how various flow variables - economic, environmental, or social, are tweaked. This form of architectural form making holds similarities to complex systems in terms of how entities are framed: less as objects in and of themselves, and more as responsive, adaptive agents.
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    Many cities around the world self-build without top-down control. What do these processes have in common with complexity?

    Cities around the world are growing without the capacity of top-down control. Informal urbanism is an example of bottom-up processes that shape the city. Can these processes be harnessed in ways that make them more effective and productive?
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    Across the globe we find spatial clusters of similar economic activity. How does complexity help us understand the path-dependent emergence of economic clusters?

    Evolutionary Economic Geography (EEG) tries to understand how economic agglomerations or clusters emerge from the bottom-up. This branch of economics draws significantly from principles of complexity and emergence, seeing the rise of particular regions as being path-dependent, and trying to understand the forces at work that drive change for economic agents - the firms that make up our economic environment.
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  • This is a list of Key Concepts that Local Interactions is related to.

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  • There would be some thought experiments here.

    Navigating Complexity © 2015-2021 Sharon Wohl, all rights reserved. Developed by Sean Wittmeyer
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