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We develop a computational framework for risk mitigation in high population density events. With increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed and results in inconvenience and tragic events. Motivated by these issues, we propose an agent-based mathematical model describing realistic human motion and simulating large dense crowds in a wide variety of events as a potential simulation testbed to trial crowd management plans. The developed model incorporates stylized mindset characteristics as an internal drive for physical behavior such as walking, running, and pushing. Furthermore, the model is combined with a visualisation of crowd movement. We develop analytic tools to quantify crowd dynamic features. The analytic tools will enable verification and validation to empirical evidence and surveillance video feed in both local and holistic representations of the crowd. This work addresses research problems in computational modeling of crowd dynamics, specifically: understanding and modeling the impact of a collective mindset on crowd dynamics versus mixtures of heterogeneous mindsets, the effect of social contagion of behaviors and decisions within the crowd, the competitive and aggressive pushing behaviors, and torso and steering dynamics.

abstract: The main objective of mathematical modeling is to connect mathematics with other scientific fields. Developing predictable models help to understand the behavior of biological systems. By testing models, one can relate mathematics and real-world experiments. To validate predictions numerically, one has to compare them with experimental data sets. Mathematical modeling can be split into two groups: microscopic and macroscopic models. Microscopic models described the motion of so-called agents (e.g. cells, ants) that interact with their surrounding neighbors. The interactions among these agents form at a large scale some special structures such as flocking and swarming. One of the key questions is to relate the particular interactions among agents with the overall emerging structures. Macroscopic models are precisely designed to describe the evolution of such large structures. They are usually given as partial differential equations describing the time evolution of a density distribution (instead of tracking each individual agent). For instance, reaction-diffusion equations are used to model glioma cells and are being used to predict tumor growth. This dissertation aims at developing such a framework to better understand the complex behavior of foraging ants and glioma cells. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2019

In this research project, we introduced an agent-based banking system based on systematic trust. The features of the model and attributes of the agents are defined and analyzed precisely, and the results are explained. Some of this model's features include but are not limited to considering the savings system, insurance deposits, the impact of the Central Bank loans, and correlated regional shocks in a banking system. Different Scenarios are applied. The results indicate that by having the Central Bank loans in the model, the banking system experience dramatically fewer failures. Even if some correlated regional shocks occur, the system can be more stable than when the Central Bank does not exist. Moreover, the trust system establishes and forms during different financial periods based on the bank's clients’ point of view about the bank's performance as an intelligent system to attract more capital for the system by providing some information for the agents to join the more prestigious banks. Conclusively, in the early financial periods, banks need more financial supports to support the clients’ deposits and to make their reputation for attracting more clients; hence the Central Bank is an essential parameter to help the banks to be more stable and supports the banks in their early stages of growth. The Central Bank loans would be significantly important in panic times, such as regional correlated preference shocks. / Thesis / Master of Science (MSc)

Yes / Agent-based modeling techniques are ideal for modeling massive complex systems such as insect colonies or biological cellular systems and even cities. However these models themselves are extremely complex to code, test, simulate and analyze. This paper discusses the challenges in using agent-based models to model complete cities as a complex system. In this paper we argue that Cities are actually a collection of various complex models which are themselves massive multiple systems, each of millions of agents, working together to form one system consisting of an order of a billion agents of different types - such as people, communities and technologies interacting together. Because of the agent numbers and complexity challenges, the present day hardware architectures are unable to cope with the simulations and processing of these models. To accommodate these issues, this paper proposes a Tera (to denote the order of millions)-modeling framework, which utilizes current technologies of Cloud computing and Big data processing, for modeling a city, by allowing infinite resources and complex interactions. This paper also lays the case for bringing together research communities for interdisciplinary research to build a complete reliable model of a city.

Desde os primeiros anos do século XXI mais da metade da população mundial passou a habitar em regiões urbanas. Este processo de urbanização, acelerado a partir da revolução industrial, trouxe consigo benefícios inegáveis à humanidade, mas também possui externalidades evidentes como o congestionamento, a violência e a segregação. Preocupada com estes problemas, surge a ciência do planejamento urbano, ora atuando na antecipação dos fatos, ora remediando os problemas existentes, utilizando as mais variadas propostas que partem de correntes de pensamento compostas por estudiosos das cidades que, nesta difícil tarefa, procuram embasamento em experiências anteriores ou em estudos que invariavelmente envolvem outras áreas de conhecimento, como sociologia, economia e engenharia. Paralelamente a estes esforços, surge nos últimos 40 anos, outra área de conhecimento, denominada Sistemas Complexos, para estudar fenômenos físicos, biológicos, econômicos e sociais, entre outros, utilizando as técnicas provenientes da dinâmica não linear, da física estatística e da computação baseada em agentes, e que vem sendo progressivamente aplicada ao estudo das cidades. Neste trabalho é realizada uma breve revisão da história do surgimento e da evolução das cidades, apresentada na seção 2, e em seguida, na seção 3, é apresentada a teoria dos sistemas complexos, descrevendo as principais características dos sistemas que podem ser analisados à ótica desta área de conhecimento. Na seção 4 é exposto o embasamento teórico e empírico que permite a fusão entre as duas ciências (Planejamento Urbano e Sistemas Complexos). Na seção 5 são reproduzidos alguns estudos computacionais da expansão urbana, consolidados na literatura científica que utilizam técnicas inerentes à ótica de sistemas complexos. Na seção 6 é proposto um modelo computacional simplificado que permite a visualização, extração de dados e análise da ocupação territorial com ênfase no estudo do custo de deslocamento no interior de um centro urbano, permitindo a conclusão, apresentada na seção 7, de que a cidade é um sistema complexo e que a abordagem através da união das áreas de conhecimento é promissora quando trata de assuntos relativos à expansão urbana, podendo ser de grande valor na elaboração de propostas que visem a amenização ou eliminação das externalidades que há tempo têm sido motivo de preocupação para os habitantes dos centros urbanos. / Since the beginning of the XXI century, more than half of the world population lives in urban areas. This process, accelerated with the industrial revolution, brought undeniable advantages, but also several handicaps, externalities such as traffic jams, violence and segregation. Concerned with these problems, a Urban Planning science is developed, acting in the effects as well as in the causes of the problems. In this task, the scientists use tools originated in several fields, such as economy, sociology and engineering. Meanwhile, in the last four decades, a different approach appears. It is called Complex Systems theory, targeted to deal with complex physical, biological, economical and social phenomena, utilizing techniques borrowed from the Non-linear dynamics, from the Statistical physics and from the Agent based models. It has been progressively applied to the Urban Planning science. This work reviews the appearance and development of the cities in the section 2, and in the section 3, the principles of Complex Systems theory are presented. In the section 4 it is showed that the Urban Planning science can profit from the Complex Systems approach. Section 5 reproduces some previous early computational models from the literature. This work contribution is presented next, in the section 6, a simplified model, based on Complex System approach, which allows visualization and urban occupation analyses in function of the transportation costs. The last section concludes that the view of the city as a complex system has many advantages when dealing with the urban expansions and the externalities arising from this process.

O objetivo deste trabalho é estudar como a distribuição de investidores entre aleatórios, grafistas, fundamentalistas e híbridos afeta a dinâmica de um mercado de ações representada por fatos estilizados. Para realização desse trabalho, foi desenvolvido um simulador de mercado de ações baseado em agentes, no qual são incorporadas regras e características do mercado de ações da BM&FBOVESPA. Os agentes grafistas, fundamentalistas e híbridos aprendem com a experiência. O simulador foi executado um número de vezes para diversas distribuições de perfis e os resultados foram analisados com o objetivo de identificar relações entre tais distribuições e os fatos estilizados estudados / The objective of this work is to study how the distribution of investors among random, chartists, fundamentalists and hybrids affects the dynamics of a stock market represented by stylized facts. To carry out this work, we developed a stock market simulator based on agents, which incorporates rules and characteristics of the BM&FBOVESPA stock market. Chartists, fundamentalists and hybrids agents can learn from experience. The simulation was performed a number of times for various profiles distributions and the results were analyzed in order to identify relationships between these distributions and the stylized facts studied

Nosso estudo foi elaborado a partir de uma analogia do modelo de Ising em duas dimensões para analisar a influência que a rede de contatos e as forças externas podem exercer no indivíduo para que ele tenha ou não a intenção de agir licitamente. Esse estudo teve como inspiração o modelo proposto no artigo Analysing Tax Evasion Dynamics Via The Ising Model (ZAKLAN; WESTERHOFF; STAUFFER, 2009), porém, com ênfase à intenção dos agentes, que precede a conduta delituosa, e não ao cometimento do crime em si, quando já ocorreu o dano à sociedade. A analogia e inclusão de algumas variáveis ao referido modelo nos possibilitou estudar, de acordo com cada cenário, formas de manter ou reduzir os índices criminais, prever possíveis situações de histerese, suas consequências e possíveis custos para a sociedade e para o governo. / Our study was drawn from an analogy of the Ising model in two dimensions to analyze the influence that the network and the external forces can exert on the individual so that whether or not he intends to act lawfully. This study was inspired by that proposed in the article \"Analysing Tax Evasion Dynamics Via The Ising Model\" (ZAKLAN; WESTERHOFF; STAUFFER, 2009) model, but with emphasis on the intention of the agents, which precedes the criminal conduct, not to the commission of the crime itself, when the damage has already occurred to society. The analogy is the inclusion of some variables that model allowed us to study, according to each scenario, ways to maintain or reduce crime rates, predict possible situations hysteresis, their consequences and potential costs to society and the government.

Nosso estudo foi elaborado a partir de uma analogia do modelo de Ising em duas dimensões para analisar a influência que a rede de contatos e as forças externas podem exercer no indivíduo para que ele tenha ou não a intenção de agir licitamente. Esse estudo teve como inspiração o modelo proposto no artigo Analysing Tax Evasion Dynamics Via The Ising Model (ZAKLAN; WESTERHOFF; STAUFFER, 2009), porém, com ênfase à intenção dos agentes, que precede a conduta delituosa, e não ao cometimento do crime em si, quando já ocorreu o dano à sociedade. A analogia e inclusão de algumas variáveis ao referido modelo nos possibilitou estudar, de acordo com cada cenário, formas de manter ou reduzir os índices criminais, prever possíveis situações de histerese, suas consequências e possíveis custos para a sociedade e para o governo. / Our study was drawn from an analogy of the Ising model in two dimensions to analyze the influence that the network and the external forces can exert on the individual so that whether or not he intends to act lawfully. This study was inspired by that proposed in the article \"Analysing Tax Evasion Dynamics Via The Ising Model\" (ZAKLAN; WESTERHOFF; STAUFFER, 2009) model, but with emphasis on the intention of the agents, which precedes the criminal conduct, not to the commission of the crime itself, when the damage has already occurred to society. The analogy is the inclusion of some variables that model allowed us to study, according to each scenario, ways to maintain or reduce crime rates, predict possible situations hysteresis, their consequences and potential costs to society and the government.

O objetivo deste trabalho é estudar como a distribuição de investidores entre aleatórios, grafistas, fundamentalistas e híbridos afeta a dinâmica de um mercado de ações representada por fatos estilizados. Para realização desse trabalho, foi desenvolvido um simulador de mercado de ações baseado em agentes, no qual são incorporadas regras e características do mercado de ações da BM&FBOVESPA. Os agentes grafistas, fundamentalistas e híbridos aprendem com a experiência. O simulador foi executado um número de vezes para diversas distribuições de perfis e os resultados foram analisados com o objetivo de identificar relações entre tais distribuições e os fatos estilizados estudados / The objective of this work is to study how the distribution of investors among random, chartists, fundamentalists and hybrids affects the dynamics of a stock market represented by stylized facts. To carry out this work, we developed a stock market simulator based on agents, which incorporates rules and characteristics of the BM&FBOVESPA stock market. Chartists, fundamentalists and hybrids agents can learn from experience. The simulation was performed a number of times for various profiles distributions and the results were analyzed in order to identify relationships between these distributions and the stylized facts studied