1. Model City Model City A study of the value of simulation and modeling as a tool for urban planners, politicians, and citizens A research proposal submitted to the Urban Studies and Planning Program Senior Sequence Class 2010-2011 \ Abstract RESEARCH QUESTION: What are the the benefits and feasibility of using computer modeling as a tool for city planners, politicians, and citizens, to comprehend, predict, and manipulate urban processes and functions? Systems thinking is an approach for developing models to facilitate our understanding of complex concepts, patterns of behavior, and the underlying structure responsible for the patterns of behavior. With respect to the city, phenomena like economic growth, taxes, population density, and zoning, are rendered as algorithms that are visible, dynamic, spatial processes occurring on the computer screen according to the rules by which they function in the city. By creating a computer game simulation of an existing city in real time and real space, citizens, politicians, and city planners, will gain greater understanding for how the mechanisms of the city work, and how they can work for and against the citizens. This will produce better informed voters and more honest politicians. The program proposed will have a realtime statistical feed feature where users can look up information layered on top of the built environment, and a hypothetical game-like scenario where users can manipulate and interact with systems within the city. This paper has found that optimization and predictive algorithms, along with realtime statistical feeds have been used in several peerreviewed case studies related to urban planning, returning highly accurate results. Further, the transparency of computer programming language renders any assumption or error immediately visible at the exact step in which it occurs in the program 1.By being able to manipulate and control the city ʼ s functions, users gain insight into how those functions work. Thus, learning how the program works through interaction will allow the user to experience how what the program simulates is working. 2.The user experiences the city as a mapping of statistical information rather than a dynamic complex of systems and interactions that produce these statistics. 3.This predictive algorithm has worked with 98% accuracy in its 3-year trial for predicting the urban development of the cities of New Jersey and Chicago. 4.The optimization algorithms were tested for strength of data, and compared to actual economic and environmental impacts from 1990- 2007 in Shanghai. These results returned 96% accuracy, based on the actual trajectory taken by Shanghai ʼ s urban growth (Zhang, 2010, 17). Findings (Corresponding by number to the above case studies) This paper uses four case studies from peer reviewed scholarly articles and journals to demonstrate the effectiveness of each of the four components in the proposed urban simulation: 1.SimCity 2007 2. WikiCity 3.“An economic agent-based model of coupled housing and land markets (CHALMS)” 4.“Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China” Methods and Materials http://artoftheiphone.com/ 2010/04/07/review-simcity/ http://umbc.academia.edu/N icholasMagliocca/Papers http://senseable.mit.edu/ wikicity/rome/ The usefulness of urban models lies in the fact that they simplify reality, putting it into a form that we can comprehend. But a truly comprehensive model of a complete system would be just as complex as that system and just as inscrutable. The map is not the territory—and a map as detailed as the territory would be of no use. So computer programs, like cities, are made up of several tiny systems of behavior that return results. At each step, those results are interactive and comprehensible. This is what computer programming offers in understanding the complex system of the city. Conclusions University of California at San Diego, Urban Studies and Planning Program USP 187 Section # 451143 Josh Van Zak March 10, 2011 http://www.metspacelab.com/