2006 Dozier Award Winner / Agent-based models can provide paleoanthropologists with a view of behavioral dynamics and site formation processes as they unfold in digital caricatures of past societies and paleoenvironments. This paper argues that the agent-based methodology has the most to offer when used to conduct controlled, repeatable experiments within the context of behavioral laboratories. To illustrate the potential of this decidedly heuristic approach, I provide a case study of a simple agent-based model currently being used to investigate the evolution of Plio-Pleistocene hominin food sharing in East Africa. The results of this null model demonstrate that certain levels of ecological patchiness can facilitate the evolution of even simple food sharing strategies among equally simple hominin foragers. More generally, they demonstrate the potential that agent-based models possess for helping historical scientists act as their own informants as to what could have happened in the past.

Rising oil prices have been a concern for both developed and developing countries, especially in more recent years as it tends to have a crippling effect on production and transportation. Many countries have moved towards the development of fossil fuel alternatives as a means of achieving energy independence and achieving environmental targets (for example the Kyoto Protocol). Developments in both these types of energy markets (fossil fuel and renewable fuels) may impact Canadian Prairie agriculture. Most of Canadian prairie crops are exported. The Canadian prairies are land locked to some extent. The closest ocean access to the eastern portion of the prairies is the port of Churchill, but is closed during the winter season. Crops are therefore transported west through the Rocky Mountains or east through the Great Lakes to get to a port. This requires hundreds of kilometres of truck and rail transportation, which is fuel dependent. To a lesser extent, at the micro-level farmers depend on fossil fuels to operate machinery to facilitate efficient crop production. If oil prices continue on an upward trajectory, will farmers cropping behaviour change? Furthermore, the development of the bioethanol industry on the Canadian prairies has given wheat farmers another crop option. As oil prices increase, the price of ethanol increases as well. Also, demand is bolstered by renewable fuel standards and government tax exemptions or subsidies. This study seeks to put forward the notion that as oil prices increase, crop production and transportation costs also increase thereby reducing farmers’ gross margins. Also, ceteris paribus, as oil prices increase there will be an increased demand for, and an increase in the price of biofuels thereby increasing the price of biofuel feedstock. Higher feedstock prices are expected to increase the gross margins of farmers. Therefore higher oil prices drive increased crop competition between traditional cropping (cropping for food exports) and energy cropping. This thesis seeks to ascertain at what level of oil prices would farmers, in general, be willing to switch from producing wheat for traditional (hard/food wheat) purposes to bioenergy (soft/ biofuel wheat) cropping alternatives. Also under varying scenarios of oil price growth and government support to the biofuel industry, this thesis seeks to ascertain the impact of biofuel industry expansion on grain elevator pricing behaviour and the structure of the elevator industry, assuming elevators spatially compete with each other for farmers’ crops. An agent based model (ABM) is employed for this study. The model is selected over other types as the researcher wants to capture the increased complexity stemming from the competition between crops that belong to at least one distribution chain. Agent based networks allow for emergent behaviour that is obtained from the spatial competition of elevators. Finally, the agent based model allows for spatial heterogeneity in location of farmers in terms of soil quality and their proximity to an elevator, which affects crop productivity and transportation costs, respectively. The ABM (also called the FARMCHAIN model) is comprised of over 35000 farmer agents, 176 elevator agents, 6 canola crushing plant agents, 5 ethanol plant agents and 1 biodiesel plant agent located on the 20 census agricultural regions (CARs) of Saskatchewan. Farmers allocate land based on their expected gross margins. Farmers produce and truck crops to the designated distribution chain. Crops move through the chain and at every stage the associated costs are computed and apportioned to the farmer. At the end of the period, gross margins are computed and these gross margins are used in computing the expected gross margins for the subsequent period. It is found that real annual crude prices would have to be greater than $133 before farmers begin to switch to producing biofuel wheat (soft wheat) from food wheat (hard wheat). This would have to be approximately 30% higher than that of 2008 in which crude prices were at record levels. Also, if biofuel support is declining then it would take a considerably higher price to entice farmers, in aggregate, to switch.

<p>Agent-based models (ABMs) are computational models used to simulate the behaviors, </p><p>actionsand interactions of agents within a system. The individual agents </p><p>each have their own set of assigned attributes and rules, which determine</p><p>their behavior within the ABM system. These rules can be</p><p>deterministic or probabilistic, allowing for a great deal of</p><p>flexibility. ABMs allow us to</p><p>observe how the behaviors of the individual agents affect the system</p><p>as a whole and if any emergent structure develops within the</p><p>system. Examining rule sets in conjunction with corresponding emergent</p><p>structure shows how small-scale changes can</p><p>affect large-scale outcomes within the system. Thus, we can better</p><p>understand and predict the development and evolution of systems of</p><p>interest. </p><p>ABMs have become ubiquitous---they used in business</p><p>(virtual auctions to select electronic ads for display), atomospheric</p><p>science (weather forecasting), and public health (to model epidemics).</p><p>But there is limited understanding of the statistical properties of</p><p>ABMs. Specifically, there are no formal procedures</p><p>for calculating confidence intervals on predictions, nor for</p><p>assessing goodness-of-fit, nor for testing whether a specific</p><p>parameter (rule) is needed in an ABM.</p><p>Motivated by important challenges of this sort, </p><p>this dissertation focuses on developing methodology for uncertainty</p><p>quantification and statistical inference in a likelihood-free context</p><p>for ABMs. </p><p>Chapter 2 of the thesis develops theory related to ABMs, </p><p>including procedures for model validation, assessing model </p><p>equivalence and measuring model complexity. </p><p>Chapters 3 and 4 of the thesis focuses on two approaches </p><p>for performing likelihood-free inference involving ABMs, </p><p>which is necessary because of the intractability of the </p><p>likelihood function due to the variety of input rules and </p><p>the complexity of outputs.</p><p>Chapter 3 explores the use of </p><p>Gaussian Process emulators in conjunction with ABMs to perform </p><p>statistical inference. This draws upon a wealth of research on emulators, </p><p>which find smooth functions on lower-dimensional Euclidean spaces that approximate</p><p>the ABM. Emulator methods combine observed data with output from ABM</p><p>simulations, using these</p><p>to fit and calibrate Gaussian-process approximations. </p><p>Chapter 4 discusses Approximate Bayesian Computation for ABM inference, </p><p>the goal of which is to obtain approximation of the posterior distribution </p><p>of some set of parameters given some observed data. </p><p>The final chapters of the thesis demonstrates the approaches </p><p>for inference in two applications. Chapter 5 presents application models the spread </p><p>of HIV based on detailed data on a social network of men who have sex with</p><p>men (MSM) in southern India. Use of an ABM</p><p>will allow us to determine which social/economic/policy </p><p>factors contribute to thetransmission of the disease. </p><p>We aim to estimate the effect that proposed medical interventions will</p><p>have on the spread of HIV in this community. </p><p>Chapter 6 examines the function of a heroin market </p><p>in the Denver, Colorado metropolitan area. Extending an ABM </p><p>developed from ethnographic research, we explore a procedure </p><p>for reducing the model, as well as estimating posterior </p><p>distributions of important quantities based on simulations.</p> / Dissertation

Complex systems offer broad, unique research challenges due to their inability to be understood through a classic reductionist perspective, as they exhibit emergent phenomena that arise through the interactions of their components. In this thesis, we briefly review some characteristics of complex systems and the interplay of mathematical and computational methods to study them. We then discuss these approaches, how they are implemented, and how they support one another in three settings. First, we present a study that connects weather data to seasonal population-abundance of mosquitoes, using a microscopic model. Secondly, we consider the collective motions that arise in ensembles of disks interacting through non-elastic collisions and investigate how such behaviors affect macroscopic transport properties. Finally, we consider a 'self-sorting' one-dimensional collection of point-particles. In all of these cases, agent-based models and simulations are used to guide analysis, and in the final example, we explain how the simulations led to new theorems. Articles and molecular dynamics computer codes are provided as appendices.

No description available.

We are recently witnessing an increase in large-scale micro/individual/- granular level behavioural data. Such data has been proven to have the capacity to aid the development of more accurate simulations that will ef- fectively predict the behaviours of complex systems. Despite this increase, the literature has failed to produce a structured modelling approach that will effectively take advantage of such granular data, in modelling com- plex systems that involve social phenomenons (i.e. social complex sys- tems). In this thesis, we intend to bridge this gap by answering the question of how novel structural frameworks, that systematically guides the use of micro-level behaviour and attribute data, directly extracted from the ba- sic entities within a social complex system can be created. These frame- works should involve the systematic processes of using such data to di- rectly model agent attributes, and to create agent behaviour rules, that will directly represent the unique micro entities from which the data was ex- tracted. The objective of the thesis is to define generic frameworks, that would create agent based micro simulations that would directly reflect the target complex system, so that alternative scenarios, that cannot be inves- tigated in the real system, and social policies that need to be investigated before being applied on the social system can be explored. In answering this question, we take advantage of the pros of other model- ing techniques such as micro simulation and agent based techniques in cre- ating models that have a micro-macro link, such that the micro behaviour that causes the macro emergence at the simulation’s global level can be easily investigated. which is a huge advantage in policy testing. We also utilized machine learning in the creation of behavioural rules.This created agent behaviours that were empirically defined. Therefore, this thesis also answers the question of how such structural framework will empirically create agent behaviour rules through machine learning algorithms. In this thesis we proposed two novel frameworks for the creation of more accurate simulations. The concepts within these frameworks were proved using case studies, in which these case studies where from different so- cial complex systems, so as to prove the generic nature of the proposed frameworks. In concluding of this thesis, it was obvious that the questions posed in the first chapter had been answered. The generic frameworks had been created, which bridged the existing gap in the creation of accurate mod- els from the presently available granular attribute and behavioral data, al- lowing the simulations created from these models accurately reflect their target social complex systems from which the data was extracted from.

<div>In recent years, there has been considerable growth in the adoption and technology development of electric vehicles (EV), autonomous vehicles (AV), and ride sharing (RS). These technologies have the potential to improve transportation sustainability. Many studies have evaluated the environmental impacts of these technologies but the existing literature has three major gaps: (1) the adoption of these three technologies need to be evaluated considering their impact on each other, (2) many existing models do not evaluate systems on a common ground, and (3) the heterogeneous preferences of riders towards these emerging technologies are not fully incorporated. To address these gaps, this work studies and quantifies the environmental and efficiency gains that can be gained through these emerging transportation technologies by developing a Parameterized Preference-based Shared Autonomous Electric Vehicle (PP-SAEV) agent-based model. The model is then applied to a case study of New York City (NYC) taxis to evaluate the system performance with increasing AV, EV, and RS adoption.</div><div><br></div><div>The outputs from the PP-SAEV model show that replacing taxi cabs in NYC with AVs along with RS potentially can reduce CO\textsubscript{2} emissions by 866 metric Tones per day and increase average vehicle occupancy from 1.2 to 3 persons in vehicles with passenger seating capacity of 4. A prediction model based on the PP-SAEV output recommends that 6000 vehicles are needed to maintain the current level of service with 100\% AV and RS adoption using capacity 4 taxis. Taxi fleets with capacity 4 with high RS and low AV adoption are also found to have the least CO\textsubscript{2} emissions. Because the heterogeneous sharing preferences of riders have shown as the major limiting factor to ride sharing, these heterogeneous sharing preferences are further modelled. The results show that high service levels are achieved when all the riders are open to sharing, and the maximum service level is reached when 30\% of riders will only accept shared rides and 70\% of the riders are either indifferent to sharing or prefer to use ride sharing over riding alone. Additionally, the service level and waiting time of riders that are inflexible (will accept only shared or non-shared rides) are greatly impacted by varying mix of riders with different sharing preference. Finally, an optimization model was built to site charging stations in a system with continually increasing EV adoption. Using the best charging station locations, transforming a fleet of autonomous or traditional vehicles to electric vehicles does not significantly change the system service level. The results show that increasing the EV adoption in fleets with 100\% RS and AV adoption reduced the daily CO\textsubscript{2} emissions by about 861 Tones and transforming a fleet of traditional taxi cabs to electric taxi cabs reduced the daily CO\textsubscript{2} emissions by 1100 Tones.</div><div><br></div><div>In summary, this dissertation evaluates the potential growth of autonomous vehicles, ride sharing, and electric vehicles in systems where riders may have heterogeneous sharing preferences, from a system performance`s perspective and assesses the environmental impacts. The developed model and the insights gained from this study can inform policy makers to develop sustainable transportation systems incorporating the emerging transportation technologies.</div>

O objetivo da presente pesquisa foi verificar se a flexibilidade característica dos modelos baseados em agentes (Agent Based Models ABM) representa adequadamente mercados em concorrência imperfeita, identificando novos elementos referentes ao comportamento e adaptabilidade dos agentes econômicos não identificados em pesquisas anteriores. Para tal, foram propostos dois modelos distintos aplicados aos mercados de passagens aéreas e sucroalcoleiro. A complexidade dos mercados analisados deve-se à forma não trivial com que é descrita a estrutura de disposição dos agentes e a maneira como estes se relacionam e tomam suas decisões, tornando infactível a aplicação de soluções analíticas. Tal fato justifica o emprego dos modelos baseados em agentes devido a sua alta flexibilidade para adequação ao ambiente simulado. O fator comum aos dois modelos propostos foi a incorporação de incertezas e expectativas nos cenários avaliados pelos agentes para sua tomada de decisão. Ao considerar as incertezas dos cenários prospectivos, os modelos simulados mostraram-se aderentes à natureza probabilística encontrada nos mercados reais, permitindo obter resultados com tendências semelhantes aos mercados estudados. A complexidade dos mercados em concorrência imperfeita analisados foi, dessa maneira, bem representada pelos modelos sugeridos. O processo adaptativo dos agentes às mudanças de mercado mostrou que os modelos baseados em agentes são ferramentas adequadas para o estudo dos mesmos e permitem captar peculiaridades dos mercados não incorporadas em outras pesquisas, revelando, inclusive características não aparentes e não incluídas em estudos anteriores. / The objective of this research was to investigate if imperfect competitive markets are well represented by the flexibility of the Agent Based Models (ABM). Therefore, it is expected that the ABM allows identifying agents new behaviour element, as well as incorporating agents adaptability processes not previously described by the other researches. Two distinct models were developed. The first one refers to the airfare prices, while the second one aims to simulate the ethanol market. The high complexity of the studied markets due to their non-trivial structure regarding the way the agents relate to each other and take their decisions justifies the employment of ABM, since ABMs are remarkably characterized by their flexibility. The common factor among the models is the incorporation of uncertainties and expectations in the models when the economic scenarios are considered by the agents for decision making. The results showed that the simulated models reached the same tendency of prices and production observed by the real data, respectively to the airfare and ethanol models. The adaptive process of the agents to the market conditions showed that ABMs are adequate tools for the study of imperfect markets, since for both models non-apparent characteristics have emerged.

Este trabalho possui um duplo objetivo: i) estudar os fatos estilizados do livro de ofertas dos papéis negociados na Bolsa de Valores de São Paulo (BOVESPA), assim como dos retornos engendrados pela dinâmica do livro de ofertas e ii) desenvolver um modelo de livro de ofertas baseado em agentes com o propósito de reproduzir tais fatos estilizados. Trabalhou-se com dados de junho/2006 a janeiro/2009 de uma amostra formada pelos vinte papéis mais negociados da BOVESPA. Os resultados empíricos corroboraram alguns fatos estilizados observados no estudo de papéis de outros países, mas refutaram outros. O modelo baseado em agentes conseguiu emular satisfatoriamente os fatos estilizados relacionados aos retornos, mas em se tratando da reprodução dos fatos estilizados do livro de ofertas o modelo foi menos eficaz. / This study has two aims: i) analyze the stylized facts of the order book of stocks traded in the São Paulo Stock Exchange (BOVESPA), as well as of the returns engendered by the order book dynamics and ii) develop an order book agent-based model able to reproduce such stylized facts. It was used data from June 2006 to January 2009 regarding a sample composed by the twenty most traded stocks in BOVESPA. The empirical results corroborated some stylized facts observed in stocks of other countries, but refuted others. The agent-based model successfully emulated the stylized facts concerning the returns; however, the model was less efficient in reproducing the stylized facts of the order book.

A generalização de modelos de crescimento por meio de um parâmetro de controle foi primeiramente proposta por Richards, em 1959. Em nosso trabalho, propomos uma forma alternativa de generalização obtendo uma interpretação emp rica e outra microscopica do parâmetro de controle. Mais especificamente, quando consideramos a proliferacão de c elulas, o parâmetro est a relacionado ao alcance da interação e a dimensão fractal da estrutura celular. Obtemos a solucão anal ítica para esta equação diferencial. Mostramos que, atrav és da escolha apropriada da escala conseguimos o colapso de dados representando a independência em relacão aos parâmetros e as condições iniciais. Al ém disso, ao considerarmos a taxa de esforco como a retirada de indiví duos de uma população, podemos associ á-la ao tratamento visando extinguir uma populacãoo de c élulas cancerosas. Em modelos epidemiol ogicos, propomos modelar a dinâmica de transmissão da dengue utilizando equacões diferenciais ordin árias. Em nosso modelo, levamos em conta tanto a dinâmica do hospedeiro quanto a do vetor, assim temos o controle da dinâmica de ambas as populações. Inclu ímos tamb ém no modelo o efeito \"enhancing\" com intuito de verificar sua influência na dinâmica de disseminacão da doença. O efeito \"enhancing\" é considerado uma das principais hipóteses para explicar a dengue hemorr ágica que pode levar a morte. Fizemos o estudo de um modelo epidemiol ógico da dengue com o objetivo de revelar quais são os fatores que levam a disseminação desse caso mais severo da doenca e, possivelmente, sugerir polí ticas p úblicas de sa úde para evit á-lo. Implementamos tamb ém um modelo de transmissão da tuberculose fazendo uso da modelagem computacional baseada em agentes, que oferece a possibilidade de representar explicitamente heterogeneidades em nível individual. / The generalization of growth models by means of a control parameter was first proposed by Richards in 1959. In our work, we propose an alternative way to obtainin an empirical and microscopic interpretation of control parameter. More specically, when considering the proliferation of cells, the parameter is related to the range of interaction and the fractal dimension of the cell structure. We obtain the analytical solution for this dierential equation. We show that, by appropriate choice of scale we have data collapse, representing the independence on parameters and initial conditions. Furthermore, when considering the e ffort as rate the removal of individuals from a population, we can associate it with the treatment to extinguish cancer cells population. In epidemiological models, we propose to model the dynamics of dengue transmission using ordinary dierential equations. In our model, we take into account both the dynamics of the host and the vector, so we have control of the dynamics of both populations. We also included in the model the effect of enhancing in order to verify their inuence on the dynamics of disease spread. The effect of enhancing is considered one of the main hypotheses to explain the hemorrhagic fever that can lead to death. We study a model of epidemiology of dengue in order to reveal what are the factors that lead to the dissemination of this more severe case of the disease and, possibly suggesting public health policies to prevent it. We also implemented a model of tuberculosis transmission making use of agent-based computational modeling, which o ffers the possibility to explicitly represent heterogeneity at the individual level. This approach allows us to deal with each individual in particular, unlike the model of dierential equations, in which all individuals are in the same compartment interact in a similar way as in a mean field interaction.