Spelling suggestions: "subject:"collective decision"" "subject:"kollective decision""
11 |
Quantification and determination of the interindividual variability observed in a group of cockroaches and its implications at a collective levelPlanas-Sitjà, Isaac 10 April 2017 (has links)
In this thesis, we used the American cockroach study the relationship between animal personality and collective behaviour. These questions do not only regard domiciliary cockroaches or insects; in fact, the questions we discuss here have a large scope and concern most of the known gregarious species distributed in several taxa. One of our aims is to develop general tools, methods and analyses that could be used for the study of collective behaviour.We show evidence of personality in several behavioural traits and different contexts in the American cockroach. These behavioural differences were observed in a context without social interactions during the daytime (isolated condition) and nighttime (solitary exploration behaviour) and in a social context (rate of joining a shelter and sheltering time). Based on the short-term experiments, this personality can be understood as differences in the probability of joining a shelter. We show that the behavioural variability existing in a population of domiciliary cockroaches is very high. The composition of personalities within a group can lead to group personality – consistent differences in group behaviour. For instance, groups composed of different behavioural profiles show different collective dynamics. Regarding the long-term experiments, our results show that the individuals that were aggregated at a site that was repeatedly disturbed by a lighting stimulus during their resting period showed slow migration to a new shelter, which allowed the initial aggregation site to remain the site of choice for a few days. Moreover, the disturbance regime did not influence the group's global activity rhythm. At the individual level, we observed interindividual differences (personalities) in terms of their position prior to the disturbance but not for the different steps of the fleeing behaviour itself. In addition, we show that thigmotaxis affects the reaction time to the disturbance: individuals near the walls of the shelter react more slowly thanindividuals in the centre. Finally, an approach coupling modelling and experimental data shows that behavioural variability plays a secondary role during migration dynamics, thus highlighting the plasticity of personality traits depending on the context. / Un des comportements collectifs les plus répandus, qu’il s’agisse de vertébrés (mammifères, oiseaux, poissons), d’insectes ou encore de bactéries, est la tendance des individus à se regrouper. Les causes proximales de ces rassemblements ou agrégats, c'est-à-dire les mécanismes à leur origine, ont retenu moins d’attention que l’étude des causes ultimes. De plus, dans la plupart des études portant sur les processus d’agrégation, notamment chez notre organisme modèle, la blatte, la diversité des comportements individuels est souvent sous-estimée ou ignorée. L’objectif de cette thèse est l’étude du rôle des différences interindividuelles, également connues comme personnalité animale ou syndromes comportementales, dans les processus de prise de décision collective et notamment la formation des agrégats.Pour cela, nous avons utilisé des groupes de mâles de la blatte américaine Periplaneta americana. Ces insectes peuvent s’agréger dans un ou plusieurs abris et présenter des différences dans leur réponse au milieu, aux conspécifiques et dans le partage de l’information. Dans le cadre de prises de décisions collectives, nous avons mis en évidence une personnalité individuelle mais également au niveau du groupe. Celles-ci se manifestent dans la recherche d’un abri dont certains individus jouent un rôle clef. Nous avons montré que les groupes présentent une stabilité qui est observable au niveau de la dynamique d'agrégation et qui dépend de la distribution des personnalités au sein de ceux-ci. De plus, nous remarquons que ces différences de personnalités au sein des groupes affectent la prise de décision collective, notamment la vitesse du choix et le nombre total d’individus abrités. De manière surprenante, la composition des groupes n’affecte pas la probabilité que ceux-ci atteignent un consensus: la majorité des blattes étant agrégées sous le même abri.Concernant les influences croisées entre l’effet sociale et la personnalité des blattes, nous montrons que les effets sociaux tendent à supprimer les différences inter-individuelles et créent une corrélation entre le comportement de chaque individu et le comportement du groupe. De plus, nous observons que la présence de différentes personnalités dans un groupe augmente les amplifications sociales, celles-ci étant dues aux interactions entre les membres du groupe. Finalement, nous abordons la question du rôle de la personnalité sur le comportement de fuite lors des perturbations lumineuses et sur la dynamique d’émigration quand le site de repos est régulièrement perturbé. Nous avons montré l’existence de personnalités exprimées pendant la phase active nocturne et de différences interindividuelles au niveau du thigmotactisme pendant la journée (phase passive de repos et d’agrégation). Curieusement, ces différences inter-individuelles ne sont pas observées lors du comportement de fuite et au niveau de la dynamique global d’émigration. Dans la dernière partie de notre thèse, nous discutons, en particulier, des synergies et des conflits entre les différentes personnalités et les dynamiques collectives et avançons l’hypothèse que les phénomènes que nous avons mis en évidence sont partagés par de nombreuses espèces grégaires. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished
|
12 |
On the design of self-organized decision making in robot swarmsCampo, Alexandre 24 May 2011 (has links)
In swarm robotics, the control of a group of robots is often fully distributed and does not rely on any leader. In this thesis, we are interested in understanding how to design collective decision making processes in such groups. Our approach consists in taking inspiration from nature, and especially from self organization in social insects, in order to produce effective collective behaviors in robot swarms. We have devised four robotics experiments that allow us to study multiple facets of collective decision making. The problems on which we focus include cooperative transport of objects, robot localization, resource selection, and resource discrimination. <p><p>We study how information is transferred inside the groups, how collective decisions arise, and through which particular interactions. Important properties of the groups such as scalability, robustness, and adaptivity are also investigated. We show that collective decisions in robot swarms can effectively arise thanks to simple mechanisms of imitation and amplification. We experimentally demonstrate their implementation with direct or indirect information transfer, and with robots that can distinguish the available options partially or not at all. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished
|
13 |
Three Empirical Analyses of VotingSong, Chang Geun 17 June 2022 (has links)
To evaluate voting rules, it would be good to know what universe election outcomes are drawn from. Election theorists have postulated that elections might be drawn from various stochastic preference models, including the IC and IAC conditions, but these models induce empirically contradicted predictions. We use two distinct data sets, FairVote and German Politbarometer survey. Based on the data information, we suggest approaches that differ from those probabilistic models to better approximate the actual data in Chapter 3 and 4.
Chapter 5 applies the spatial model for four-candidate in a three-dimensional setting. We also offer a significant gap between the actual and simulated data under the IAC conditions by comparing their statistical characteristics. / Doctor of Philosophy / Through the 1884 Third Reform Act, the plurality rule (or first-past-the-post system) runs to elect parliament members for the first time. More than a hundred years passed after the Act, and election theorists have suggested various alternatives, the plurality rule is the second most used rule worldwide for national elections for now. One main reason is that researchers do not reach an agreement on the best alternative rule. Theorists have evaluated different voting rules under probabilistic assumptions, but real-world examples contradict the predictions of these models. In this dissertation, we suggest different approaches provide a better approximation to the actual data. In Chapter 3 and 4, we go backward: analyze how voters of each preference order are distributed in real data first, then set a model for estimating the frequency of paradox. In chapter 5, we extend an existing model with higher dimensionality. Then using the model, we offer empirical evidence showing the gap between the actual and simulated data under a popular probabilistic model.
|
14 |
Mathematical modelling approach to collective decision-makingZabzina, Natalia January 2017 (has links)
In everyday situations individuals make decisions. For example, a tourist usually chooses a crowded or recommended restaurant to have dinner. Perhaps it is an individual decision, but the observed pattern of decision-making is a collective phenomenon. Collective behaviour emerges from the local interactions that give rise to a complex pattern at the group level. In our example, the recommendations or simple copying the choices of others make a crowded restaurant even more crowded. The rules of interaction between individuals are important to study. Such studies should be complemented by biological experiments. Recent studies of collective phenomena in animal groups help us to understand these rules and develop mathematical models of collective behaviour. The most important communication mechanism is positive feedback between group members, which we observe in our example. In this thesis, we use a generic experimentally validated model of positive feedback to study collective decision-making. The first part of the thesis is based on the modelling of decision-making associated to the selection of feeding sites. This has been extensively studied for ants and slime moulds. The main contribution of our research is to demonstrate how such aspects as "irrationality", speed and quality of decisions can be modelled using differential equations. We study bifurcation phenomena and describe collective patterns above critical values of a bifurcation points in mathematical and biological terms. In the second part, we demonstrate how the primitive unicellular slime mould Physarum Polycephalum provides an easy test-bed for theoretical assumptions and model predictions about decision-making. We study its searching strategies and model decision-making associated to the selection of food options. We also consider the aggregation model to investigate the fractal structure of Physarum Polycephalum plasmodia. / <p>Fel serie i tryckt bok /Wrong series in the printed book</p>
|
15 |
Etude des processus décisionnels lors des déplacements collectifs chez le cheval domestique (Equus ferus caballus) / Decision-making processes during collective movements in domestic horses (Equus ferus caballus)Briard, Léa 28 September 2015 (has links)
La vie en groupe représente de nombreux défis pour les animaux et l’un d’entre eux est le maintien de la cohésion groupe. Comment les animaux décident collectivement vers où et quand se déplacer,se nourrir, se reposer alors qu’ils n’ont pas les mêmes motivations ou besoins ? Dans ce travail de thèse je me suis intéressée aux mécanismes qui sous-tendent les décisions collectives lors des déplacements chez le cheval domestique et notamment le poids des différences interindividuelles et des relations sociales sur ces mécanismes. Pour cela, j’ai étudié quatre groupes de chevaux contenant uniquement des juments ou des groupes familiaux contenant un étalon et des juments.J’ai pu mettre en évidence 1) l’absence de leader et l’existence de décision partagée par l’ensemble du groupe, 2) l’importance de la personnalité et des relations sociales sur les décisions, 3) l’impact de la période précédant le départ sur la rapidité du consensus et 4) la coexistence de mécanismes auto-organisés et individualisés. Enfin en étudiant plus précisément les étalons, j’ai pu montrer quecontrairement à l’idée populaire, ils ne sont pas les leaders de leur groupe. Leur rôle s’apparente plus à celui d’un surveillant et ils sont parfois un des catalyseurs du phénomène. Ces résultats suggèrent que les chevaux vivent au sein d’un système hybride ou décisions partagée et non partagée coexistent. / Living in groups is challenging on many levels for animals and one of this challenge is the maintenance of group cohesion. How animals that do not share the same motives or needs, decide collectively where and when to go, to rest or to eat? In this work, I studied the mechanisms underlying collective decision during group movements in domestic horses, and notably the weight of interindividual differences and social relationships on those mechanisms. In order to achieve thatgoal, I studied four groups of domestic horses containing only females or one male and several females (i.e. natural group organisation). I was able to show that in horses 1) there is no leader and the decision is shared among group members, 2) personality and social relationships play a key role on the individual decisions, 3) the period before departure is crucial in determining the speed of the consensus, 4) both individualized and self-organised mechanisms underlie collective decisions. Finally by studying thoroughly the behaviour of stallions, I was able to debunk the myth that stallionsare the leader of their group. Their role is closer to that of a supervisor and sometimes of a catalyseras they can push females forward. Overall these results suggest that horses live in a hybrid system where shared and unshared decision coexist.
|
16 |
The Best-of-n Problem in Robot SwarmsValentini, Gabriele 04 July 2016 (has links)
Collective decision making can be seen as a means of designing and understanding swarm robotics systems. While decision-making is generally conceived as the cognitive ability of individual agents to select a belief based only on their preferences and available information, collective decision making is a decentralized cognitive process, whereby an ensemble of agents gathers, shares, and processes information as a single organism and makes a choice that is not attributable to any of its individuals. A principled selection of the rules governing this cognitive process allows the designer to define, shape, and foresee the dynamics of the swarm.We begin this monograph by introducing the reader to the topic of collective decision making. We focus on artificial systems for discrete consensus achievement and review the literature of swarm robotics. In this endeavor, we formalize the best-of-n problem—a generalization of the logic underlying several cognitive problems—and define a taxonomy of its possible variants that are of interest for the design of robot swarms. By leveraging on this understanding, we identify the building-blocks that are essential to achieve a collective decision addressing the best-of-n problem: option exploration, opinion dissemination, modulation of positive feedback, and individual decision-making mechanism. We show how a modular perspective of a collective decision-making strategy allows for the systematic modeling of the resulting swarm performance. In doing so, we put forward a modular and model-driven design methodology that allows the designer to study the dynamics of a swarm at different level of abstractions. Successively, we employ the proposed design methodology to derive and to study different collective decision-making strategies for the best-of-n problem. We show how the designed strategies can be readily applied to different real-world scenarios by performing two series of robot experiments. In the first series, we use a swarm of 100 robots to tackle a site-selection scenario; in the second series, we show instead how the same strategies apply to a collective perception scenario. We conclude with a discussion of our research contributions and provide futuredirection of research. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished
|
17 |
La collégialité en droit des sociétés / Collegiality in corporate lawDelvallée, Julien 22 May 2017 (has links)
Notion fondamentale du droit des sociétés, la collégialité est souvent réduite aux organes sociaux, voire cantonnée au processus de formation des décisions collectives. L'étude tend à dépasser la dimension institutionnelle du pouvoir collégial. Il s'agit de rechercher, en dépit de la diversité des collèges, les fondements, l'unité, le régime, les limites et la valeur de la collégialité en tant que notion et pratique. À cette fin, il convient d'envisager autant l'organisation collégiale que le fonctionnement collégial. Il en résulte que toute collégialité suppose une pluralité de personnes ou des collèges (au moins deux) (1) qui ensemble et à égalité par voie de délibération en concertation (2), poursuivent la réalisation d'un projet commun ou l'exécution d'une mission commune (3). Toutefois il existe deux catégories de collégialité selon ce qui fait l'unité du collège: projet commun (associés) ; fonction ou mission commune (autres organes). Ce qui fait l'unité du collège influence la nature et l'intensité des droits et obligations que toute organisation collégiale suppose pour ses membres. Il en est de même du fonctionnement. Unitaire en ce qu'il renvoie au processus de formation de l'acte collectif unilatéral, le fonctionnement collégial suppose des techniques variables selon chaque figure. Enfin, la collégialité est-elle un principe du droit des sociétés ? Pour les associés, cela est certain : la collégialité renvoie au groupement qu'ils forment, organisation et fonctionnement, sans qu'une prévision en ce sens ne soit nécessaire. Pour les autres organes la réponse est variable. Elle n'est un principe d'organisation et de fonctionnement qu'autant qu'une norme l'impose. / Collegiality, as the pivotal concept in corporate law, is often limited to the corporate bodies, if not confined to the collective decision-making process. The study tends to go beyond the institutional dimesion of the collegial authority. The aim is to investigate the foundations, the unity, the ambit, the limits and the value of collegiality as both a notion and a practice, in spite of the variety of colleges. To this end, the collegial organization and function should be considered equally. As a result, collegiality means a plurality of persons or colleges (at least two) (1) who, together and equally by conciliated deliberation (2), promote the realization of a collaborative project or the performance of a shared mission (3). However, there are two types of collegiality as defined by the college's unity itself: there are collaborative projects (partners) ; and shared missions or functions (other bodies). The essence and the strength of rights and obligations to each of the members is influenced by what makes the unity of a college. The same thing goes for the way in which the collegial organization functions. It will function in a unitary manner for unilateral establishment and collective acts. A collegial functioning, on the other hand, supposes flexible and adjustable techniques. Finally is collegiality a principle of corporate law ? For the partners this is obvious: collegiality is intrinsic to the group they constitute, to the organization and to their functioning, without having to plan it. For the other bodies the answer may vary. Collegiality is only a principle of organization and functioning if a norm requires it to be.
|
18 |
Déplacements collectifs auto-organisés : décision individuelle et transfert d'information / Self-organized collective movements : individual decision and information transferToulet, Sylvain 13 November 2015 (has links)
Les déplacements collectifs se manifestent souvent de façon spectaculaire et intriguent tant les amateurs de la nature que les chercheurs. Comment émergent ces formes spectaculaires et comment la cohésion des groupes est elle assurée ? Si de nombreux travaux ont été consacrés à l'identification des règles permettant la cohésion dans les groupes en mouvement, plus rares sont ceux consacrés aux transitions entre les états d'arrêt et de déplacement. Cette thèse traite des mécanismes comportementaux impliqués dans les prises de décisions collectives et la dynamique de transition de tels évènements chez le mouton Merinos (Ovis aries). Nous proposons de nouvelles hypothèses sur la modulation des interactions entre individus par des effets spatiaux dans des groupes de grande taille. Nous proposons un modèle spatio-temporel reproduisant nos résultats expérimentaux sur les départs, les déplacements collectifs et les arrêts de groupes de taille croissante et permettant d'explorer les décisions collectives dans des conditions nouvelles. Les résultats expérimentaux et théoriques per- mettent d'améliorer la compréhension des mécanismes individuels à l'origine des décision collectives permettant de maintenir ou non la cohésion des groupes. / Collective movements often involve very spectacular displays that fascinate nature lovers and researchers. How do such amazing patterns appear and how group cohesion can be maintained ? If many studies were carried out to decipher the rules underlying cohesion for groups in movement, there is a lack of works adressing the transitions involved in collective movements : departures and stops. This thesis adresses the behavioural mechanisms involved in the collective decision-making processes oc- curing in such transitions in Merino sheep (Ovis aries) groups. We propose some new kinds of spatial hypotheses that can account for the way interactions between individuals are locally modulated in large groups where individuals cannot have an access to the global information of all individuals. We developed a novel spatiotemporal model of sheep collective motion that reproduces the experimental observations and allows to explore the outcomes of collective decisions in various conditions. The experimental and theoretical results increase the understanding of the individual mechanisms that produce collective decisions allowing to maintain group cohesion.
|
19 |
Incremental social learning in swarm intelligence systemsMontes De Oca Roldan, Marco 01 July 2011 (has links)
A swarm intelligence system is a type of multiagent system with the following distinctive characteristics: (i) it is composed of a large number of agents, (ii) the agents that comprise the system are simple with respect to the complexity of the task the system is required to perform, (iii) its control relies on principles of decentralization and self-organization, and (iv) its constituent agents interact locally with one another and with their environment. <p><p>Interactions among agents, either direct or indirect through the environment in which they act, are fundamental for swarm intelligence to exist; however, there is a class of interactions, referred to as "interference", that actually blocks or hinders the agents' goal-seeking behavior. For example, competition for space may reduce the mobility of robots in a swarm robotics system, or misleading information may spread through the system in a particle swarm optimization algorithm. One of the most visible effects of interference in a swarm intelligence system is the reduction of its efficiency. In other words, interference increases the time required by the system to reach a desired state. Thus, interference is a fundamental problem which negatively affects the viability of the swarm intelligence approach for solving important, practical problems.<p><p>We propose a framework called "incremental social learning" (ISL) as a solution to the aforementioned problem. It consists of two elements: (i) a growing population of agents, and (ii) a social learning mechanism. Initially, a system under the control of ISL consists of a small population of agents. These agents interact with one another and with their environment for some time before new agents are added to the system according to a predefined schedule. When a new agent is about to be added, it learns socially from a subset of the agents that have been part of the system for some time, and that, as a consequence, may have gathered useful information. The implementation of the social learning mechanism is application-dependent, but the goal is to transfer knowledge from a set of experienced agents that are already in the environment to the newly added agent. The process continues until one of the following criteria is met: (i) the maximum number of agents is reached, (ii) the assigned task is finished, or (iii) the system performs as desired. Starting with a small number of agents reduces interference because it reduces the number of interactions within the system, and thus, fast progress toward the desired state may be achieved. By learning socially, newly added agents acquire knowledge about their environment without incurring the costs of acquiring that knowledge individually. As a result, ISL can make a swarm intelligence system reach a desired state more rapidly. <p><p>We have successfully applied ISL to two very different swarm intelligence systems. We applied ISL to particle swarm optimization algorithms. The results of this study demonstrate that ISL substantially improves the performance of these kinds of algorithms. In fact, two of the resulting algorithms are competitive with state-of-the-art algorithms in the field. The second system to which we applied ISL exploits a collective decision-making mechanism based on an opinion formation model. This mechanism is also one of the original contributions presented in this dissertation. A swarm robotics system under the control of the proposed mechanism allows robots to choose from a set of two actions the action that is fastest to execute. In this case, when only a small proportion of the swarm is able to concurrently execute the alternative actions, ISL substantially improves the system's performance. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished
|
20 |
Influence in combinatorial and collective decision-making : by the example of UN security council voting / Phénomènes d'influence dans des situations de prise de décision collective : l'exemple des votes au conseil de sécurité del'ONULuo, Hang 05 June 2015 (has links)
L'objet de cette thèse (bi-disciplinaire, en informatique et sciences politiques) est l'étude de phénomènes d'influence dans des situations de prise de décision collective, impliquant plusieurs sujets interdépendants, ce qui amène à considérer des domaines dits combinatoires. L'importance de ces phénomènes d'influence est observée depuis de nombreuses années dans différents domaines (dont les sciences politiques), mais leur modélisation reste peu développée jusqu'à présent. En se basant sur un modèle existant intégrant la prise en compte de l'influence à un langage de représentation des préférences ordinal, le premier travail de cette thèse a été d'identifier des schémas d'influences pouvant survenir, entre sujets et/ou agents différents. Une deuxième contribution de cette thèse est la prise en compte de domaines partiels (permettant de représenter contraintes exogènes et abstentions, par exemple), une nécessité dans les situations envisagées. De même, différents modèles visant à capturer l'influence simultanée de plusieurs agents sont présentés et discutés. Dans un deuxième temps, l'exemple des votes au conseil de sécurité del'ONU est utilisé: l'occurence de ces schémas est envisagée à l'aide d'une analyse qualitative de différentes séquences de votes (sciences politiques), et de la recherche d'indices de schémas similaires dans les données de vote accessibles. Enfin, le modèle est mobilisé dans le cadre d'une simulation multi-agents (réalisée en Netlogo), et visant à tester différentes réformes envisagées du conseil de sécurité. / Influence study in combinatorial and collective decision-making, is an interdisciplinary research area combining computer science and social science, especially artificial intelligence and collective decision-making. Influence has long been studied, for instance in political science, but in the context of combinatorial and collective decision-making, this calls for a study of how influences works among multi-agents and multi-issues, how influences and decision-making are interleaved, and how the structures of influence among agents and issues produce an effect. In the thesis, we mainly performed three aspects of work:Firstly, build complex models of influence based on preference representation languages and social influence models, proposed a series of new patterns of influence to better describe the complex influences in real-world situation, and discussed a series of theoretical problems of influencing and influenced structure, influence from more than one origins, and influence with abstentions and constraints. We then test the models of influence from an exemplary perspective for interdisciplinary study, from both social science and computer science paradigms, by both qualitative case studies approach and quantitative matching algorithms approach, to provide an evaluation for the models of influence.Finally, we use the models of influence to perform agent-based simulations, by the example UN Security Council voting. We design those experiments from both social and computer science perspectives, implement it in Netlogo, and discuss the interleaved effects between new cases of influence and different SC reform schemes.
|
Page generated in 0.1007 seconds