Dans cette thèse, nous nous sommes intéressés à l'impact de la quantité et de la qualité de l'information échangée entre individus d'un groupe sur leurs performances collectives dans deux types de tâches bien spécifiques. Dans une première série d'expériences, les sujets devaient estimer des quantités séquentiellement, et pouvaient réviser leurs estimations après avoir reçu comme information sociale l'estimation moyenne d'autres sujets. Nous contrôlions cette information sociale à l'aide de participants virtuels (dont nous contrôlions le nombre) donnant une information (dont nous contrôlions la valeur), à l'insu des sujets. Nous avons montré que lorsque les sujets ont peu de connaissance préalable sur une quantité à estimer, (les logarithmes de) leurs estimations suivent une distribution de Laplace. La médiane étant un bon estimateur du centre d'une distribution de Laplace, nous avons défini la performance collective comme la proximité de la médiane (du logarithme) des estimations à la vraie valeur. Nous avons trouvé qu'après influence sociale, et lorsque les agents virtuels fournissent une information correcte, la performance collective augmente avec la quantité d'information fournie (fraction d'agents virtuels). Nous avons aussi analysé la sensibilité à l'influence sociale des sujets, et trouvé que celle-ci augmente avec la distance entre l'estimation personnelle et l'information sociale. Ces analyses ont permis de définir 5 traits de comportement : garder son opinion, adopter celle des autres, faire un compromis, amplifier l'information sociale ou au contraire la contredire. Nos résultats montrent que les sujets qui adoptent l'opinion des autres sont ceux qui améliorent le mieux leur performance, car ils sont capables de bénéficier de l'information apportée par les agents virtuels. Nous avons ensuite utilisé ces analyses pour construire et calibrer un modèle d'estimation collective, qui reproduit quantitativement les résultats expérimentaux et prédit qu'une quantité limitée d'information incorrecte peut contrebalancer un biais cognitif des sujets consistant à sous-estimer les quantités, et ainsi améliorer la performance collective. D'autres expériences ont permis de valider cette prédiction. Dans une seconde série d'expériences, des groupes de 22 piétons devaient se séparer en clusters de la même "couleur", sans indice visuel (les couleurs étaient inconnues), après une courte période de marche aléatoire. Pour les aider à accomplir leur tâche, nous avons utilisé un système de filtrage de l'information disponible (analogue à un dispositif sensoriel tel que la rétine), prenant en entrée l'ensemble des positions et couleurs des individus, et retournant un signal sonore aux sujets (émit par des tags attachés à leurs épaules) lorsque la majorité de leurs k plus proches voisins était de l'autre couleur que la leur. La règle consistait à s'arrêter de marcher lorsque le signal stoppait. / In this thesis, we were interested in the impact of the quantity and quality of information ex- changed between individuals in a group on their collective performance in two very specific types of tasks. In a first series of experiments, subjects had to estimate quantities sequentially, and could revise their estimates after receiving the average estimate of other subjects as social information. We controlled this social information through virtual participants (which number we controlled) giving information (which value we controlled), unknowingly to the subjects. We showed that when subjects have little prior knowledge about a quantity to estimate, (the loga- rithms of) their estimates follow a Laplace distribution. Since the median is a good estimator of the center of a Laplace distribution, we defined collective performance as the proximity of the median (log) estimate to the true value. We found that after social influence, and when the information provided by the virtual agents is correct, the collective performance increases with the amount of information provided (fraction of virtual agents). We also analysed subjects' sensitivity to social influence, and found that it increases with the distance between personal estimate and social information. These analyses made it possible to define five behavioral traits: to keep one's opinion, to adopt that of others, to compromise, to amplify social information or to contradict it. Our results showed that the subjects who adopt the opinion of others are the ones who best improve their performance because they are able to benefit from the infor- mation provided by the virtual agents. We then used these analyses to construct and calibrate a model of collective estimation, which quantitatively reproduced the experimental results and predicted that a limited amount of incorrect information can counterbalance a cognitive bias that makes subjects underestimate quantities, and thus improve collective performance. Further experiments have validated this prediction. In a second series of experiments, groups of 22 pedestrians had to segregate into clusters of the same "color", without visual cue (the colors were unknown), after a short period of random walk. To help them accomplish their task, we used an information filtering system (analogous to a sensory device such as the retina), taking all the positions and colors of individuals in input, and returning an acoustic signal to the subjects (emitted by tags attached to their shoulders) when the majority of their k nearest neighbors was of a different color from theirs.

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.

Providing service via theWeb differs from other service provision environments in that it is possible for the unexpected arrival of a massive number of service requests in a small time-frame, a situation commonly referred to as a flash crowd. Events of this nature are beyond the control of the service provider, and have the potential to severely degrade service quality and, in the worst case, to deny service to all clients completely. The occurrence, severity and sought Web content of a flash crowd is beyond the control of service provision software. How this software reacts to such a flash crowd, however, is not. Given the short-lived nature of flash crowds, it is unreasonable to expect such systems to increase the system resources they can apply to a particular flash crowd event. It is also difficult to predict the particular nature of any flash crowd, and subsequently which system resources will bottleneck. The driving hypothesis of this research is that, if we are to reasonably expect to have software react effectively to flash crowd events, we need to alter that software at runtime to remove system bottlenecks, whilst a flash crowd event is in progress. This is a special case of what is usually known as "unanticipated software evolution". This thesis reports on an investigation into how unanticipated software evolution can be applied to running Web service provision software to remove system bottlenecks. It does so by introducing automated dynamic Web content degradation to running software currently subject to simulated flash crowd events. The thesis describes and validates appropriate runtime extensions to allow generative object communication architectures (a promising class of architecture for unanticipated software evolution) to be converted initially into a Web application server, and then later accept further runtime behaviour changes. Such changes could alter system bottlenecks by replacing the key programming logic causing system bottlenecks at runtime.

At the starting point of the work leading to this doctoral thesis, in January 2005, the work on pedestrians was almost exclusively oriented towards computer simulations and on evacuation experiments. Since then, there have been many studies on new methods for extracting empirical data of pedestrian movements (mainly based on video analysis, lasers, and infrared cameras), but most of the work is still focused on artificial setups for crowds moving through corridors and crowds passing bottlenecks. Even though these controlled experiments are important to understand crowd dynamics, there is a knowledge gap between these experiments and the understanding of the dynamics leading to and occurring during large crowd disasters, when sometimes hundreds of thousands or even millions of pedestrians are involved. Numerous crowd disasters occur every year at large gatherings around the world. Unfortunately, the information about the (spatio-temporal) development of these events tend to be qualitative rather than quantitative. Video recordings from the crowd disaster in Mina, Kingdom of Saudi Arabia, on the 12th of January 2006, where hundreds of pilgrims lost their lives during the annual Muslim pilgrimage to Makkah, gave the possibility to scientifically evaluate the dynamics of the crowd. With this video material, it was possible to observe and analyze the behavior of the crowd under increasing crowd density, leading to the disaster. Based on the insights from the analysis of the crowd disaster described above, new tools and measures to detect and avoid critical crowd conditions have been proposed, and some of them have been implemented in order to reduce the likelihood of similar disasters in the future. Further contributions of this thesis are to empirically evaluate many of the previous assumptions used for pedestrian simulations. These assumptions are: * A pedestrian avoids collisions by changing her or his walking speed by an acceleration which is exponentially decaying with the distance to the pedestrian or object being avoided. * A pedestrian reacts stronger to what happens in front of her or him, than to what happens behind the back. * The movement of a crowd of pedestrians always follows a smooth flow-density relationship, called the fundamental diagram. * The walking speed will settle at 0 m/s at a specific maximum crowd density. The first two assumptions were found to be consistent with the data, but the pedestrian-flow theory had to be revised, since the two latter assumptions do not always hold. When these fundamental parts of pedestrian motion and avoiding maneuvers had been investigated, an improved version of the social-force-model was formulated. In order to enable the revision of previous works and the analysis of the crowd disaster mentioned above, algorithms used for video-tracking have been introduced. The novelty of this work concerns the uniqueness and quantity of data on which the algorithms are validated and calibrated, but also the focus on analyzing millions of pedestrians rather than hundreds. The aim of this thesis is to move from theoretical models and controlled lab conditions to applicable models for real-world conditions. / Als diese Dissertation im Januar 2005 begonnen wurde, nutzten wissenschaftliche Untersuchungen von Fußgängern fast ausschließlich Computersimulationen und Evakuierungsexperimente. Seit dem haben viele Wissenschaftler an einer Verbesserung der Methoden gearbeitet. Heute werden empirische Daten mit Hilfe von Videoanalysen, Laser- und Infrarotkameras erhoben.Jedoch konzentrieren sich viele dieser Arbeiten auf künstliche Setups, in denen sich Fußgängermassen durch Korridore und Engpässe bewegen. Diese Experimente erlauben es, Massenbewegungen zu verstehen. Jedoch gibt es immer noch Forschungslücken. Es ist schwierig, unter solch kontrollierten Bedingungen Fortschritte darin zu erzielen, die auftretenden Dyamiken bei großen Katastrophen zu verstehen, in denen manchmal Hunderttausende oder sogar Millionen von Fußgängern involviert sind. Immer wieder kommt es zu Katastrophen in großen Menschenmengen. Leider sind von diesen Ereignissen häufig nur qualitative Informationen anstelle von quantitativen Daten erhältlich. Es ergab sich die besondere Gelegenheit, quantitatives Filmmaterial über eine Katastrophe in Mina (Königreich Saudi--Arabien) zu erhalten. Dort starben am 12. Januar 2006 hunderte von Pilgern während der jährlichen muslimischen Pilgerfahrt nach Mekka. Mit dem erhobenen Videomaterial konnte nachvollzogen werden, wie die Menschenmenge zuerst unbehindert fließen konnte, dann immer dichter wurde und wie es schließlich zur Katastrophe kam. Von den Erkenntnissen der Analyse der oben beschriebenen Katastrophe konnten neue Methoden entwickelt werden, die dabei helfen können, ähnliche Katastrophen in Zukunft zu vermeiden. Ein weiterer Beitrag dieser Dissertation besteht darin, einige Annahmen, die üblicherweise bei der Simulation von Fußgängerdynamiken gemacht werden, in Frage zu stellen und zu überarbeiten. Diese Annahmen sind: (1) Ein Fußgänger verhindert Zusammenstöße, indem er seine Schrittgeschwindigkeit so verändert, dass seine Beschleunigung exponentiell mit der Distanz zu dem zu umgehenden Fußgänger oder Objekt abnimmt. (2) Ein Fußgänger zeigt stärkere Reaktionen auf Ereignisse, die vor ihm passieren, als auf Ereignisse, die hinter ihm passieren. (3) Die Bewegung eines in einer Menschenmenge befindlichen Fußgängers folgt immer dem Strömungs--Dichte Verhältnis, was als Fundamental-Diagramm bezeichnet wird. (4) Die Laufgeschwindigkeit eines Fußgängers erreicht bei maximaler Menschendichte einem Wert von 0 m/s. Die ersten beiden Annahmen wurden von den empirischen Daten bestätigt. Unsere Analysen zeigen jedoch, dass die Annahmen 3 und 4 nicht immer gültig sind. Somit müssen Standardtheorien von Fußgängerdynamiken überarbeitet werden. Im Anschluß an die Analyse dieser fundamentalen Aspekte von Fußgängerverhalten und dem Verhalten bei Ausweichmanövern wird das Social-Force-Modell weiterentwickelt. Um auf vorhergehenden Arbeiten aufzubauen und um die oben beschriebene Katastrophe analysieren zu können, werden Algorithmen für die Video-Verfolgung von Fußgängerbewegungen entwickelt. Das Neue bei diesem Teil der Arbeit liegt nicht nur in dem verwendeten Verfahren selbst, sondern auch in der Einzigartigkeit und der großen Menge an verwendeten Daten, die mit diesem Verfahren analysiert werden. Ein zentrales Ziel dieser Arbeit besteht demnach in einer wissenschaftlichen Weiterentwicklung von theoretischen Modellen und kontrollierten Laborexperimenten hin zu Modellen, die unter realen Bedingungen tatsächlich anwendbar sind. Die Analyse von Fußgängern ist ein interdisziplinäres Feld, das von verschiedenen wissenschaftlichen Disziplinen mit verschiedenen Zielen betrieben wird. Leider gab es bislang wenig Bemühungen, die Resultate innerhalb dieser Teilgebiete im Rahmen einer konsistenten Theorie zu vereinen. Als seltene Ausnahmen können die Arbeiten von Teknomo und Antonini genannt werden. Diese Dissertation verfolgt das Ziel, diese theoretische Vereinigung weiter voran zu treiben. Dazu muss man zwischen der Neuerfindung des Rades und der Wiederverwendung nicht geprüfter Resultate abwägen. Dementsprechend ist ein Teil dieser Dissertation dem Vorhaben gewidmet, bisherige Forschung im Lichte empirischer Daten und neuer Methoden zu evaluieren. Da sich die Arbeit mit recht unterschiedlichen Aspekten von Fußgängerverhalten beschäftigt, konzentriert sich die Analyse in verschiedenen Teilen der Arbeit auf einige ausgewählte, alternative Modelle. Insbesondere bei der Modellierung und Simulation wird anstelle einer eingehenden Übersicht verschiedener Modelle eine Diskussion des speziellen Social-Force Modells präsentiert.

Crowdsourcing can today be found in practically any industry, but the extent to which it is used differ widely. A report from last year, published by the crowdsourcing platform eYeka (eYeka 2015b), shows that the fashion industry is among the industries using crowdsourcing the least. Brands that are more inclined to using crowdsourcing are those working with fast moving consumer goods (FMCG). That includes many brands from the food & beverage industry such as Coca-Cola, Pepsi, Danone etc. This study builds on this knowledge to explore the use of crowdsourcing in the food & beverage industry to find out if that experience can be used in the fashion industry where it is not widely used today. To identify different approaches of crowdsourcing used in the food & beverage industry 78 crowdsourcing campaigns from 9 brand during a two years period (2014-2015) was analysed. The analysis resulted in the identification of 3 main approaches: crowdsourcing as ideation, customer engagement and crowdsourcing for creation/production. More importantly this study comes to the conclusion that the way crowdsourcing is used by the brands in the food & beverage industry is not formed in such a way that it is exclusive to the industry in question. There are no immediate boundaries for the fashion industry to adopt the same way of working. If the fashion industry would like to follow the trend in food & beverage industry they should focus more on the creative ideation side of crowdsourcing and less on the creation, and most of all on marketing. However, there are also other areas they can learn from like Business Development.

Wie Menschen von anderen lernen und wann es adaptiv-rational ist sich auf soziales Lernen zu verlassen sind wichtige Fragen in vielen Disziplinen einschließlich der Psychologie, der Biologie, der Anthropologie und den Wirtschaftswissenschaften. Trotz der geteilten Interessen dieser Disziplinen sind viele der vorhandenen Resultate voneinander isoliert und oft nicht vergleichbar, teilweise weil es der Forschung zum sozialen Lernen immer noch eines theoretischen Rahmens fehlt, welcher die gewonnen Erkenntnisse vergleichbar machen würde sowie erklären würde warum unterschiedliche Strategien in Abhängigkeit vom sozialen Kontext erfolgreich sind oder nicht. In meiner Arbeit schlage ich einen solchen theoretischen Rahmen vor, welcher sich auf der Forschung zur ökologischen Rationalität gründet. Ich benutze den theoretischen Rahmen der ökologischen Rationalität sozialen Lernens, um drei Fragen zu beantworten: i) Wie können soziale Lernstrategien als kognitiv plausible Strategien modelliert werden, die auf drei einfachen Building Blocks beruhen (Such-, Stopp- und Entscheidungsregeln), ii) was sind die wichtigsten Faktoren von sozialen Umwelten und Problemumwelten, in denen soziales Lernen stattfindet und iii) wie interagieren soziale Lernstrategien, die auf unterschiedlichen Building Blocks beruhen, mit der Struktur von Umwelten, um unterschiedliche Erfolgsniveaus zu erreichen. Indem ich diese drei Fragen adressiere, erarbeite ich die Bedingungen unter denen unterschiedlichen Strategien adaptiv-rational sind und erkläre wie unterschiedlichen Strategien in bestimmten Umwelten erfolgreich sind. Jedes der Kapitel behandelt eine wichtige alltägliche soziale Lernsituation, identifiziert die Schlüsselcharakteristiken der Situation und demonstriert wie die Building Blocks des sozialen Lernens mit diesen Umweltstrukturen interagieren, um unterschiedliche Erfolgsniveaus zu erreichen. / How people learn from others and when it is adaptive to rely on social learning have been major questions in several disciplines including psychology, biology, anthropology and economics. Despite the shared interest of these diverse fields, many of the results remain isolated and are often incomparable, in part because the study of social learning still lacks a general theoretical framework that would make results comparable or explain why different strategies perform well in different contexts. In this thesis I propose such a framework that is grounded in the study of ecological rationality. I use this frame- work to explore three primary questions: i) how can social learning strategies be modeled as cognitively plausible strategies composed of simple building blocks (search, stopping and decision rules), ii) what are key characteristics of social and task environments in which social learning takes place, and iii) how do social learning strategies composed of different building blocks interact with the structure of the environment to produce different levels of success. Through addressing these three questions I map out the conditions under which different strategies are adaptive and explain how the building blocks of different strategies contribute to their performance in certain environments. The thesis focuses on three representative classes of social learning strategies, namely, frequency-dependent, payoff-biased, and unbiased copying. Different chapters focus on important everyday social learning settings, identify key environmental characteristics defining the setting and demonstrate how the building blocks of social learning strategies interact with these environmental structures to produce different outcomes.

Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2018-09-13T13:02:14Z No. of bitstreams: 1 ESTEVAO SMANIA TESTA_DIS.pdf: 3237172 bytes, checksum: d5aadd66e71bcae6b9ef00c5c31e0e5a (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-09-14T19:04:09Z (GMT) No. of bitstreams: 1 ESTEVAO SMANIA TESTA_DIS.pdf: 3237172 bytes, checksum: d5aadd66e71bcae6b9ef00c5c31e0e5a (MD5) / Made available in DSpace on 2018-09-14T19:26:34Z (GMT). No. of bitstreams: 1 ESTEVAO SMANIA TESTA_DIS.pdf: 3237172 bytes, checksum: d5aadd66e71bcae6b9ef00c5c31e0e5a (MD5) Previous issue date: 2018-03-15 / Planos de evacua??o t?m sido historicamente usados como uma medida de seguran?a para a constru??o de edif?cios. Os simuladores existentes requerem ambientes 3D totalmente modelados e tempo suficiente para preparar e simular cen?rios. Uma vez que a quantidade de pessoas pode mudar ao longo do tempo, v?rias simula??es s?o frequentemente necess?rias para gerar um plano de evacua??o otimizado. Neste documento ? apresentado uma nova abordagem para estimar os dados resultantes de um dado cen?rio de evacua??o sem simula-lo de fato. Para tal o ambiente ? dividido o ambiente em salas modulares com configura??es diferentes, em um estilo divis?o e conquista. Em seguida, uma rede neural artificial ? treinada para estimar os dados desejados de uma sala sozinha. Ap?s coletar os dados estimados de cada sala, uma heur?stica capaz de agregar informa??es por sala ? desenvolvida para que o ambiente completo possa ser devidamente estimado. Esse m?todo apresenta erros dentro da margem de 30% quando comparado o tempo de evacua??o em um ambiente real e complexo. Al?m disso, n?o ? necess?rio modelar o ambiente 3D, aprender como configurar um simulador de multid?es e o tempo computacional para estimar ? instant?neo quando comparado ao melhor caso de um simulador de multid?es. / Evacuation plans have been historically used as a safety measure for the construction of buildings. The existing simulators require fully-modeled 3D environments and enough time to prepare and simulate scenarios. Since the amount of people in a given simulated scenario can change over time, several simulations are often required in order to generate an optimal evacuation plan. With that in mind, we present in this paper a novel approach to estimate the resulting data of a given evacuation scenario without actually simulating it. For such, we divide the environment into modular rooms with different configurations, in a divide-and-conquer fashion. Next, we train an artificial neural network to estimate all required data regarding the evacuation of a single room. After collecting the estimated data from each room, we developed a heuristic capable of aggregating per room information so the full environment can be properly evaluated. Our method presents errors within the 30% margin when compared to evacuation time in a real and complex environment. In addition, it is not necessary to model the 3D environment, learn how to use and configure a crowd simulator, and the computational time to estimate is instantaneous when compared to a best case real-time crowd simulator.

Par l'analyse des pratiques de l'image, artistiques et médiatiques, le texte entend mettre au jour les mécaniques de la société du spectacle, altérées par les révolutions de la technologie de l'information et de la communication. Dans les espaces virtuels, la médiatisation émerge comme la modalité principale de toute forme d'interaction dématérialisée. L'image exerce sa puissance et conditionne les comportements. Pourtant, l'image peut s'opposer au flux dominant du spectacle et offrir un espace d'expression à contre-flux, contestataire et radical. Ce texte examine la consommation des représentations dans cette société du spectacle où la coercition anime la psychologie des foules - nuages fluides de particules individuelles séparées dont les mouvements chaotiques semblent imprévisibles. Cette recherche élabore une typologie des foules repensée au travers de la coercition des images, des médias et du pouvoir de la technologie sur le libre arbitre individuel. En s'appuyant sur des représentations iconiques de la violence et de la mort dans les événements visuels globaux - à l'instar de la photographie sidérante « The Falling Man » - ce texte aborde les tensions entre dispositifs, information et foules en dressant le portrait de l'Homme hypermoderne face aux foules virtuelles. Soumis au flux d'images constant, il semble en quête permanente d'une liberté insaisissable, fruit d'une identité qui peu à peu se dissipe au sein d'une société à la dérive incitant à ne vivre que par l'externalisation dans les technologies : utopie d'un Homme transparent, dépourvu d'intériorité, vivant dans l'espoir d'outrepasser la mort par la projection de soi dans le flux d'information. / Through the analysis of artistic and media-generated imagery, this text seeks to shed light on the mechanisms of the society of the spectacle, altered by the revolutions of information and communication technology. In virtual spaces, mediatization has emerged as the main modality of every dematerialized interaction. Image exercises power and conditions behaviors, but may also act counter to the dominant stream of spectacle thus opening a space for a counter-current both controversial and radical. This text examines how image is consumed in this society of the spectacle, in which coercion drives crowd psychology - fluid clouds of unique separated particles whose chaotic movements appear unpredictable. This research establishes a typology of crowds revised through the coercion of images, media, and the power of technology over individual freewill. By studying iconic images of violence and death in global visual events - as exemplified in The Falling Man, a photograph that stuns the viewer - the text raises issues concerning the seeming tensions between devices, information and crowds, while displaying the portrait of hypermodern Man in his relationship toward virtual crowds. Man, subjected to incessant streams of images, seems to be on a permanent quest for a freedom which eludes him, a consequence of an identity slowly dissipating into the mainstream. This text proposes an analysis of a society running adrift, a society offering nothing but a life of self­disembodiment into technological devices : utopia of a new transparent Man, deprived of self, living only in the hope of achieving immortality by projecting the self into the information stream.

This work results from a survey of the demonstration that took place in June 2013 in the state of Alagoas, in the city Delmiro Gouveia, in the sertão, and in Maceió, in the coast. Through this survey from the analysis of periodicals, digital, iconographic and oral sources, which aimed to understand how the demonstration by the reduction in the value of the urban public transport fare, started in São Paulo in June 2013, inspired the crowd in these cities from Alagoas to deflagrate street demonstrations in the same period, you can see that the development and statement about this event in these cities possess unique way. In this sense, on these characteristics, this dissertation discusses how the issues on posters or banners erected by the crowd in Alagoas, the news coverage of the mainstream media, the locations chosen form meetings and demonstrations, control strategies and the performance of masked in this state, they were marked political and historical meaning different from those that marked the events of June in São Paulo, Rio de Janeiro, Minas Gerais, Brasília, Bahia, among other states. / Esta dissertação resulta de uma pesquisa sobre as manifestações ocorridas em junho de 2013 no estado de Alagoas, nas cidades Delmiro Gouveia, no Sertão, e em Maceió, no Litoral. Através desta pesquisa realizada a partir da análise de periódicos e de fontes digitais, iconográficas e orais, que objetivou compreender como as manifestações pela redução no valor da tarifa do transporte coletivo urbano, iniciadas no estado de São Paulo, em junho de 2013, inspiraram a multidão destas cidades alagoanas a deflagrarem manifestações de rua neste mesmo período, pode-se visualizar que os desdobramentos e as asserções sobre este acontecimento nestas cidades possuem sentidos singulares. Neste sentido, a respeito dessas especificidades, esta dissertação discute como os temas nos cartazes ou faixas erguidas pela multidão em Alagoas, a cobertura jornalística da grande mídia, os locais escolhidos para reuniões e manisfestações, as estratégias de luta e a atuação dos mascarados neste estado, estiveram marcadas por significados políticos e históricos distintos daqueles que marcaram as manifestações de junho em São Paulo, Rio de Janeiro, Minas Gerais, Brasília, Bahia e outros estados.

Orientador: Siome Klein Goldenstein / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-16T21:25:11Z (GMT). No. of bitstreams: 1 Saboia_PriscilaCorrea_M.pdf: 2582894 bytes, checksum: 1645aa6b8b779ee7180adbbb04d23981 (MD5) Previous issue date: 2010 / Resumo: Atualmente, estima-se que a população mundial seja de cerca de seis bilhões e oitocentos milhões de habitantes (6.800.000.000), dos quais metade mora em aglomerados urbanos. Nestes centros, é corriqueiro o fen¿omeno da movimentação de multidões. Tecnicamente, entende-se multidão como um grande grupo de indivíduos em um mesmo ambiente físico, compartilhando um objetivo comum e podendo agir diferentemente do que quando estão sozinhos. Compreender a movimentação destas multidões é de vital import¿ancia para o planejamento e a melhoria dos locais públicos, não só no sentido de facilitar e agilizar o deslocamento dos cidadãos, mas também garantir-lhes segurança, especialmente em condições de perigo iminente, onde pode haver a necessidade de evacuação de tais locais. Além disso, existem várias áreas do conhecimento que têm potencial para se beneficiar do estudo do comportamento de multidões. Na indústria de entretenimento, por exemplo, simulações de multidões podem ser utilizadas na produção de animações e jogos de computador. No treinamento policial e militar, simulações podem ser usadas para demonstração e controle de rebeliões. Na área de engenharia de segurança, simulações podem ser utilizadas para estudo de desocupação emergencial de construções, navios e aviões. Em todas as áreas citadas, observa-se que a necessidade por simulações de multidões advém de duas situações que podem ocorrer no mundo real. Primeiramente, pode ser perigoso para os indivíduos realizar as ações objetivadas (como cair de um prédio em um filme, ou evacuar uma sala de cinema em chamas, por exemplo), bem como é antiético submetê-los a tais condições. Segundo, é muito complexo e oneroso lidar com um grande número de indivíduos no mundo real. Ambas as situações podem ser evitadas pela simulação computacional da situação real. Nestes termos, o objetivo desta dissertação é modelar a movimentação de multidões, tendo em vista a simulação em computador. Para tanto, sistemas multiagentes brownianos são introduzidos como uma alternativa tecnológica 'a implementação dos modelos encontrados na literatura, bem como 'a implementação de um novo modelo de movimentação de multidões, híbrido por reunir conceitos de modelos que lançam mão das chamadas forças sociais, com conceitos de modelos baseados na estratégia Lattice-Gas. Como resultado prático, um novo simulador de sistemas multiagentes construído para a tarefa de simulação de movimentação de multidões é apresentado / Abstract: Currently, it is estimated that world population is about six billion and eight hundred million inhabitants (6.8 billion), of whom half live in urban areas. In these centers, it is common the phenomenon of moving crowds. Technically, a crowd can be seen as a large group of individuals put in the same physical environment, sharing a common goal and acting differently than when they are alone. Understanding the movement of these crowds is very important for planning and improving public places, not only in order to facilitate and expedite the movement of citizens, but also in order to guarantee their safety, especially in conditions of imminent danger, where it can be necessary the evacuation of such sites. Furthermore, there are several areas of knowledge that can gain benefits from the study of crowd behavior. In the entertainment industry, for example, crowd simulations can be used to produce animations and computer games. In Police and military training, simulations can be used for demonstration and control of riots. In the area of safety engineering, simulations can be used to study the urgent evacuation of buildings, ships and aircrafts. In all mentioned areas, it is observed that the need for crowd simulations comes from two situations, taking into consideration the real world. First, it can be dangerous for individuals to perform the desired actions (like falling from a building in a movie, or evacuating the room on fire of a failing movie session). It is also unethical to expose them to such conditions. Second, it is very complex and expensive to handle a large number of individuals in the real world. Both situations can be dealt by simulating the real world into a computer. Thus, this dissertation aims to model the movement of crowds, always having in mind the computer simulation. For this, Brownian multi-agent systems are introduced as a technological alternative to implement the models found in literature, as well as to implement a new hybrid movement model, that gathers together concepts from solutions based on social forces, and solutions based on Lattice- Gas. As a practical result, a new simulator for multi-agent systems is presented, built for the task of simulating moving crowds / Mestrado / Sistemas de Informação / Mestre em Ciência da Computação