Initial context and density analysis and mapping

Project: Articulated Incentive Network (AIN)
Year: 2014
Professors: Thomas Kearns, Jordan Kanter
Partners: Reid Mauti, Jeffrey Widjaja

The Articulated Incentive Network proposes a new network of green infrastructure and clean industry for the City of Chicago.

Chicago offers a number of financial incentive programs, such as Tax Increment Financing (TIF), for developments in certain areas of the city. These developments have been largely criticized for being isolated and holding the interests of corporations or organizations, rather than unifying the communities they were meant to foster.

A.I.N. studied Constant Nieuwenhuys’ New Babylon and adapts the core ideas to the current context of city. This leaves a project entirely different from Constant’s, but is governed by similar principles.

Using data from the city and agent based modeling, the A.I.N. analyzes a program that attempts to simulate the dérive, to propose new territories and projects for Chicago’s financial incentive programs. This program searches for affinity in resources, types of people and what specific communities need. This allows for these projects to relate directly to the communities they are built in, while also emphasizing self-sufficiency, desegregation, and public transport.

UML diagram of the agent based system

Image from running program (view raw footage below)