The birth of complexity research derives from the logical progression of advancement in the scientific field afforded by reductionist theory. We present in silico models of two complex physiological processes, wound healing and coagulation/fibrinolysis based on two common tools in the study of complex physiology: ordinary differential equations (ODE) and Agent Based Modeling (ABM). The strengths of these two approaches are well-suited in the analysis of clinical paradigms such as wound healing and coagulation. The complex interactions that characterize acute wound healing have stymied the development of effective therapeutic modalities. The use of computational models holds the promise to improve our basic approach to understanding the process. We have modified an existing ordinary differential equation model by 1) evolving from a systemic model to a local model, 2) the incorporation of fibroblast activity, and3) including the effects of tissue oxygenation. Possible therapeutic targets, such as fibroblast death rate and rate of fibroblast recruitment have been identified by computational analysis. This model is a step toward constructing an integrative systems biology model of human wound healing. The coagulation and fibrinolytic systems are complex, inter-connected biological systems with major physiological roles. We present an Agent Based Modeling and Simulation (ABMS) approach to these complex interactions. This ABMS method successfully reproduces the initiation, propagation, and termination of blood clot formation and its lysis in vitro due to the activation of either the intrinsic or extrinsic pathways. Furthermore, the ABMS was able to simulate the pharmacological effects of two clinically used anticoagulants, warfarin and heparin, as well as the physiological effects of enzyme deficiency/dysfunction, i.e., hemophilia and antithrombin III-heparin binding impairment, on the coagulation system. The results of the model compare favorably with in vitro experimental data under both physiologic and pathophysiologic conditions. Our computational systems biology approach integrates reductionist experimental data into a cohesive model that allows rapid evaluation of the effects of multiple variables. Our ODE and AMBS models offer the ability to generate non-linear responses based on known relationships among variables and in silico modeling of mechanistic biological rules on computer software, respectively. Simulations of normal and disease states as well as effects of therapeutic intervention demonstrate the potential uses of computer simulation. Specifically, models may be applied to hypothesis generation and biological advances, discovery of new diagnostic and therapeutic options, platforms to test novel therapies, and opportunities to predict adverse events during drug development. The ultimate aim of such models is creation of bedside simulators that allow personalized, individual medicine; however, a myriad of opportunities for scientific advancement are opened through in silico experimentation.

Approved for public release, distribution is unlimited / The delivery of supply in combat operations is very important and often results in success or failure of a mission. This activity, as well as other transportation problems, has traditionally been modeled using global optimization techniques, such as linear programming. However, the goal of this thesis is to examine the feasibility of an agent-based solution to study the movement of material through a road network. The requirement is to build an agent-based system that finds the optimal route through a given road network and is capable of adapting to disruptions introduced to the network and then find alternative routes through the network. The agents act from a local perspective, and can represent more realistically the decisions being made throughout the delivery process. This thesis implements an analysis environment for road networks and develops an agent-based model to build truck-driver agents that are capable of delivering supplies through a changing road network. / Captain, German Army

O presente trabalho tem como objetivo analisar a dinâmica da transmissão da política monetária através dos canais de crédito (Canal de Empréstimo Bancário e Canal dos Balanços Patrimoniais), utilizando conceitos e ferramentas da área de Sistemas Complexos para simular uma economia representada por diferentes setores em que os agentes estão interconectados através de relacionamentos de crédito. O presente modelo baseia-se no trabalho de Gatti et al. (2009). A novidade foi introduzir um mecanismo de transmissão da política monetária através de um mercado interbancário e de uma taxa básica de juros permitindo analisar os impactos na economia através dos canais de crédito. O resultado da simulação mostra que o impacto das políticas monetárias no âmbito microeconômico podem se desenvolver como resultado da interação complexa desses agentes heterogêneos através de relacionamentos de crédito ao longo do tempo, e as variáveis no âmbito macroeconômico, como a taxa básica de juros, afetam o próprio sistema através de um processo de retroalimentação ou feedback. / This study aims to analyze the dynamics of the monetary policy transmission through the credit channels (Bank Lending Channel and Balance Sheets Channel), using concepts and tools from the Complex Systems field to simulate an economy represented by different sectors in which agents are interconnected via credit relationships. This model is based on the work of Gatti et al. (2009) that used agent-based modeling. The novelty was to introduce a transmission mechanism of monetary policy through an interbank market and a primary interest rate, allowing the analysis of the impacts on the economy through the credit channels. The simulation results show that the impact of monetary policy on microeconomic level can be developed as a result of the complex interaction of these heterogeneous agents via credit relationships over time, and the variables in the macroeconomic context, such as the primary interest rate, affect the system through a feedback process.

Episodes of aggression and violence continue to beset our public spaces. This thesis explores how well we understand the transition to violence—and how aggression and violence in public spaces can be managed or controlled. We begin by arguing that established social psychological approaches to aggression and violence are inadequate for the task. Existing models explain violence through the failure of individuals to inhibit their own impulses or control their own emotions sufficiently. At best the models allow for the importance of dyadic interactions as individuals provoke each other as part of an escalation cycle. We argue that public space aggression and violence involves multiple parties and more complex sets of social dynamics. We suggest that, at the very least, the roles of third-parties and social categories need to be at the heart of theorising about violence in public spaces. To support our arguments, we examined violence directly through detailed behavioural microanalyses of real-life aggressive incidents captured on CCTV footage. We also built agent-based models (ABM) to explore different theoretical approaches to the impact of groups and third-parties on aggression and violence. The thesis contains seven studies. We begin with a CCTV behavioural microanalysis (Study 1) that showed collective group self-regulation of aggressive and violent behaviour in both within- and between-group conflicts. This study demonstrated an ‘intergroup hostility bias’, showing a greater likelihood of aggressive, escalatory acts towards outgroup members in intergroup conflicts than towards ingroup members in intragroup conflicts. Furthermore, this study demonstrated an ‘intragroup de-escalatory bias’, showing a greater likelihood of peace-making, de-escalatory behaviours towards ingroup members in intragroup conflicts than towards outgroup members in intergroup conflicts. Overall, we found that the majority of coded actions were acts of de-escalation performed by third-parties. With evidence stressing the importance of social dynamics, we compared dyadic models of aggression against an alternative social model (which allowed normative influence of others) in a dynamic agent-based modelling environment. We modelled the dynamics of metacontrast group formation (Studies 2 and 3), and found that group processes can produce both escalation of violence and inhibition of violence (Study 4). We found greater polarisation of violent positions in intergroup interactions than in intragroup interactions (Studies 5a and 5b). However, an emergent intergroup hostility bias did not emerge from this polarisation process. In Study 6, we re-examined the intergroup hostility bias present in our CCTV footage. We found an intergroup hostility bias for non-physical escalatory acts but not for physical escalatory acts. We examined the standardised number of actions contributed by third-parties and assessed the relationship between specific third-party conflict management strategies (policers and pacifiers) and conflict violence severity (Study 7). Overall, our results showed that third-parties and groups are integral features of the dynamics of violence. Third-parties largely attempt to de-escalate conflict, and the conflict management strategy they employ has a direct relationship to the violent outcome. Groups have a tendency to de-escalate their own members, and self-policing and collective inhibition take place. These findings have importance for current models of aggression and violence and also for evidence-based violence reduction initiatives.

Entendimento de processos que levem ao surgimento de opiniões extremas é valioso na prevenção de atos de violência. Os modelos são ferramentas úteis para identificar possíveis padrões relacionados a estes processos. No entanto, modelos discretos ou contínuos com confiança limitada não se mostram adequados para estudar dinâmicas caracterizadas pela divergência de opiniões. É proposta uma extensão cultural do modelo de Opiniões Contínuas e Ações Discretas (CODA) com múltiplos assuntos alternados por um mecanismo de ligação preferencial. Os agentes são influenciados não só em suas opiniões, mas também nas importâncias que atribuem aos diferentes assuntos. As principais características do modelo são o surgimento de preferências e consensos locais, aos quais estão associadas as opiniões mais extremas. Há, em contrapartida, persistência de opiniões brandas nos temas menos preferidos. O estudo do espaço paramétrico do modelo revelou que modificações diminuindo a localidade das interações aumentam maiorias e amenizam opiniões. Duas estratégias distintas de debate foram testadas. Zelotes têm poder de conversão aumentado quando dispersos. Evitadores minimizam o número de interações indesejável se agrupados. Foram esboçadas abordagens para inserção de efeitos da mídia na dinâmica / Understanding processes leading to extremism is invaluable to prevent violence outbursts. Models are useful tools that allow for identifying patterns related to those processes. Nevertheless, discrete models and bounded-confidence continuous models are unfit for studying diversion-based dynamics. We present a cultural extension of CODA model, with multiple subjects selected through a preferential attachment rule. Agents are influenced in their opinions and relevance attributed to different subjects. The most notable results of the dynamics are the establishment of local subject preferences and consensus, associated with more extreme opinions. On the other hand, there is persistence of immature undeveloped opinion in the locally less regarded subjects. The study of parametric space has shown that settings reducing the locality of interactions both increase the majority size and make opinions less extreme. Two distinct debate strategies were simulated. Zealots increase conversions when spread throughout the network. In contrast, subject avoiders decrease the number of unwanted interactions by grouping together. Some ideas for introducing media influence to the model were outlined

Entendimento de processos que levem ao surgimento de opiniões extremas é valioso na prevenção de atos de violência. Os modelos são ferramentas úteis para identificar possíveis padrões relacionados a estes processos. No entanto, modelos discretos ou contínuos com confiança limitada não se mostram adequados para estudar dinâmicas caracterizadas pela divergência de opiniões. É proposta uma extensão cultural do modelo de Opiniões Contínuas e Ações Discretas (CODA) com múltiplos assuntos alternados por um mecanismo de ligação preferencial. Os agentes são influenciados não só em suas opiniões, mas também nas importâncias que atribuem aos diferentes assuntos. As principais características do modelo são o surgimento de preferências e consensos locais, aos quais estão associadas as opiniões mais extremas. Há, em contrapartida, persistência de opiniões brandas nos temas menos preferidos. O estudo do espaço paramétrico do modelo revelou que modificações diminuindo a localidade das interações aumentam maiorias e amenizam opiniões. Duas estratégias distintas de debate foram testadas. Zelotes têm poder de conversão aumentado quando dispersos. Evitadores minimizam o número de interações indesejável se agrupados. Foram esboçadas abordagens para inserção de efeitos da mídia na dinâmica / Understanding processes leading to extremism is invaluable to prevent violence outbursts. Models are useful tools that allow for identifying patterns related to those processes. Nevertheless, discrete models and bounded-confidence continuous models are unfit for studying diversion-based dynamics. We present a cultural extension of CODA model, with multiple subjects selected through a preferential attachment rule. Agents are influenced in their opinions and relevance attributed to different subjects. The most notable results of the dynamics are the establishment of local subject preferences and consensus, associated with more extreme opinions. On the other hand, there is persistence of immature undeveloped opinion in the locally less regarded subjects. The study of parametric space has shown that settings reducing the locality of interactions both increase the majority size and make opinions less extreme. Two distinct debate strategies were simulated. Zealots increase conversions when spread throughout the network. In contrast, subject avoiders decrease the number of unwanted interactions by grouping together. Some ideas for introducing media influence to the model were outlined

O presente trabalho tem como objetivo analisar a dinâmica da transmissão da política monetária através dos canais de crédito (Canal de Empréstimo Bancário e Canal dos Balanços Patrimoniais), utilizando conceitos e ferramentas da área de Sistemas Complexos para simular uma economia representada por diferentes setores em que os agentes estão interconectados através de relacionamentos de crédito. O presente modelo baseia-se no trabalho de Gatti et al. (2009). A novidade foi introduzir um mecanismo de transmissão da política monetária através de um mercado interbancário e de uma taxa básica de juros permitindo analisar os impactos na economia através dos canais de crédito. O resultado da simulação mostra que o impacto das políticas monetárias no âmbito microeconômico podem se desenvolver como resultado da interação complexa desses agentes heterogêneos através de relacionamentos de crédito ao longo do tempo, e as variáveis no âmbito macroeconômico, como a taxa básica de juros, afetam o próprio sistema através de um processo de retroalimentação ou feedback. / This study aims to analyze the dynamics of the monetary policy transmission through the credit channels (Bank Lending Channel and Balance Sheets Channel), using concepts and tools from the Complex Systems field to simulate an economy represented by different sectors in which agents are interconnected via credit relationships. This model is based on the work of Gatti et al. (2009) that used agent-based modeling. The novelty was to introduce a transmission mechanism of monetary policy through an interbank market and a primary interest rate, allowing the analysis of the impacts on the economy through the credit channels. The simulation results show that the impact of monetary policy on microeconomic level can be developed as a result of the complex interaction of these heterogeneous agents via credit relationships over time, and the variables in the macroeconomic context, such as the primary interest rate, affect the system through a feedback process.

abstract: This thesis consists of three projects employing complexity economics methods to explore firm dynamics. The first is the Firm Ecosystem Model, which addresses the institutional conditions of capital access and entrenched competitive advantage. Larger firms will be more competitive than smaller firms due to efficiencies of scale, but the persistence of larger firms is also supported institutionally through mechanisms such as tax policy, capital access mechanisms and industry-favorable legislation. At the same time, evidence suggests that small firms innovate more than larger firms, and an aggressive firm-as-value perspective incentivizes early investment in new firms in an attempt to capture that value. The Ecological Firm Model explores the effects of the differences in innovation and investment patterns and persistence rates between large and small firms. The second project is the Structural Inertia Model, which is intended to build theory around why larger firms may be less successful in capturing new marketshare than smaller firms, as well as to advance fitness landscape methods. The model explores the possibility that firms with larger scopes may be less effective in mitigating the costs of cooperation because conditions may arise that cause intrafirm conflicts. The model is implemented on structured fitness landscapes derived using the maximal order of interaction (NM) formulation and described using local optima networks (LONs), thus integrating these novel techniques. Finally, firm dynamics can serve as a proxy for the ease at which people can voluntarily enter into the legal cooperative agreements that constitute firms. The third project, the Emergent Firm model, is an exploration of how this dynamic of voluntary association may be affected by differing capital institutions, and explores the macroeconomic implications of the economies that emerge out of the various resulting firm populations. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics for the Life and Social Sciences 2018

Understanding coral disease dynamics within the heterogeneous populations in which they act is critical for predicting how the structure of reefs may change as a result of enzootic or epizootic levels of these important sources of mortality. This work focused on combining field studies and the development and testing of a spatially-explicit, individual-based epizootiological computer model with the aim of gaining a greater understanding of the dynamics and impact of white plague, a significant source of mortality on reef-building corals in the Caribbean region. Field studies focused on the incidence and distribution of all sources of coral mortality, including suspect white plague in situ, at two locations; the Florida Keys (United States of America) and Little Cayman Island (Cayman Islands, British West Indies). Results indicated that in both regions disease was the most significant source of mortality during the monitoring time periods, and that suspect white plague type II in Cayman is likely contributing to major structural changes. In Florida, observations made during a mass bleaching event indicated that a significant relationship exists between bleaching severity and disease incidence, and that mortality during the event was largely the result of disease and not bleaching. The simulation model was developed using a long-term data set from Little Cayman, and results of calibration indicated that suspect white plague type II on these reefs is transmissible between colonies within a limited field and require a yearly input from an outside source, and that host susceptibility to infection is low and likely not variable among species. Parameters describing the distribution and composition of the coral population were varied, and results indicated a significant effect of colony density, aggregation, and mean size on the impact of disease. Scenario testing of various disease management strategies indicated that should local prevention measures be developed in the future, it is they, and not treatment, that will likely be the most effective in limiting the impact of disease.

Many animal groups benefit from making decisions collectively. For example, colonies of many ant species are able to select the best possible nest to move into without every ant needing to visit each available nest site. Similarly, honey bee colonies can focus their foraging resources on the best possible food sources in their environment by sharing information with each other. In the same way, groups of human individuals are often able to make better decisions together than each individual group member can on his or her own. This phenomenon is known as "collective intelligence", or "wisdom of crowds." What unites all these examples is the fact that there is no centralized organization dictating how animal groups make their decisions. Instead, these successful decisions emerge from interactions and information transfer between individual members of the group and between individuals and their environment. In this thesis, I apply mathematical modeling techniques in order to better understand how groups of social animals make important decisions in situations where no single individual has complete information. This thesis consists of five papers, in which I collaborate with biologists and sociologists to simulate the results of their experiments on group decision-making in animals. The goal of the modeling process is to better understand the underlying mechanisms of interaction that allow animal groups to make accurate decisions that are vital to their survival. Mathematical models also allow us to make predictions about collective decisions made by animal groups that have not yet been studied experimentally or that cannot be easily studied. The combination of mathematical modeling and experimentation gives us a better insight into the benefits and drawbacks of collective decision making, and into the variety of mechanisms that are responsible for collective intelligence in animals. The models that I use in the thesis include differential equation models, agent-based models, stochastic models, and spatially explicit models. The biological systems studied included foraging honey bee colonies, house-hunting ants, and humans answering trivia questions.