Durch den demografischen Wandel leben mehr diverse ältere Menschen in Städten. Es gibt jedoch keine Modelle, die das räumliche Verhalten von Älteren simulieren, obwohl sie einen geringen Aktionsradius haben und stärker von der umgebenden Infrastruktur abhängig sind. Gleichzeitig ist nicht erforscht, wie sich die Kombination von Variablen auf die Umzugsbereitschaft auswirkt und es sind keine Datensätze verfügbar, die genügend Informationen liefern. In dieser Arbeit wurde ein Workflow entwickelt, um die städtische Dynamik einer vielfältigen älteren Bevölkerung (>=65 Jahre) mit einem empirisch fundierten Agenten basierten Modell am Beispiel Berlins zu modellieren. Zunächst wurden eine Umfrage, Experteninterviews und eine Literaturrecherche durchgeführt, um Variablen abzuleiten, die zu einem Umzug führen. Zudem wurde ein Framework angepasst, um diverse Agenten abzuleiten. Die Bevölkerung wurde mit einer Clusteranalyse in Agententypologien (AT) mit gleichem Umzugsverhalten gruppiert. Die ATs wurden mit Erwartungen verglichen, die aus Literaturrecherche und Experteninterviews abgeleitet wurden. Danach wurden räumliche Informationen mit einer räumlichen Mikrosimulation hinzugefügt. Die Variablen Alter und Unterstützungsnetzwerk wurden als Gewichte für die Berechnung der Umzugswahrscheinlichkeit der einzelnen Agenten verwendet, da diese als die wichtigsten Faktoren für einen Umzug identifiziert wurden. Die Ergebnisse der Simulation wurden mit Daten verglichen. Außerdem wurden Veränderungen in der räumlichen Verteilung analysiert. Es zeigt sich, dass sich die ATs nicht räumlich segregieren und das resultierende Modell robust ist. Der Ansatz kann auf andere Städte übertragen werden, da er auf Daten beruht, die in anderen Regionen verfügbar sind. Zudem kann das Modell als Grundlage für detailliertere Agenten oder komplexere Verhaltensregeln dienen. Zusammengefasst liefert die Arbeit einen sehr guten Ansatz zur Modellierung einer vielfältigen Bevölkerung. / In the last years, more elderly with diverse backgrounds live in cities due to demographic changes. However, there exist no models which simulate the spatial behaviour of the elderly even though they have a smaller range of action and are more dependent on their surrounding infrastructure. At the same time, there is no research on how the combination of different variables affects their willingness to move and no datasets that provide sufficient information are available. This research developed a workflow, to model the urban dynamics of a diverse elderly population (>=65 years) with an empirically grounded agent-based model for the example of Berlin. First, a survey was conducted, along with expert interviews and literature research, to derive variables and reasons that lead to relocation. Additionally, an existing framework was adapted to derive diverse agents. The population was grouped with a cluster analysis into agent typologies (AT) with the same basic relocation behaviour. The resulting artificial population was evaluated with expectations derived from literature research and expert interviews. Afterwards, spatial information was added with a spatial microsimulation. Because age and support networks were identified as the most important factors for relocation, these variables were included as weights for the calculation of the relocation probability of every individual agent. The simulation output was compared to real population data. Furthermore, changes in the spatial distribution were evaluated based on a segregation index. It is shown that ATs do not segregate themselves spatially and the resulting model is robust. The approach can be adapted to other cities because it is based on data which is available in other regions. Furthermore, the model can be a basis for more detailed agents or more complex behaviour rules. In the end, the thesis provides an approach to model a diverse population with its behaviour rules.

The push for clean energy has caused a rapid growth of renewables in the electricity supply mix of the EU. Although one would assume that the impact of these technologies is entirely positive, recent research and experience indicate that there is reason for concern namely regarding the security of supply. In this context, the concern is how renewable energy sources (RES) affect the business case of conventional power generation. In response to this concern, capacity mechanisms are being considered or have already been implemented by various member states of the EU. However, in a highly interconnected electricity system, such as the one in Europe, there appears to be a risk that the uncoordinated implementation of capacity mechanisms may cause unintended cross-border effects. This research explored the performance of various capacity mechanisms in an electricity system with a strong growth in the portfolio share of variable renewable energy sources (RES). The cross-border effects of implementing various capacity mechanisms in an interconnected power system were also analyzed. In this research, two capacity mechanisms, namely a strategic reserve and a capacity market, were modeled as extensions to the EMLab-Generation agent-based model. Furthermore, two variations of a capacity market were analyzed. The first was a yearly capacity market design and the second was a forward capacity market with long term contracts. A survey of experts on the US capacity markets supplemented the modeling work with practical insights. / <p>QC 20161006</p><p>The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively.</p><p>copyright (c) 2016 P. C. Bhagwat</p>

The Basic Income concept in the perspective of Agent-Based modelling Abstract: The thesis study the relationship between the basic income introduction and the price level. The basic income would replace the existing social security. The resulting redistribution induce changes in the aggregate demand through the concave consumption function. The aggregate demand in turn affect the price creation mechanism. Because the price level is a result of activity of many different agents with private motivation and information, the work used a simple macroeconomic agent-based model to isolate the relationship. The simulation however did not succeed in isolating the possible link between the price level and the basic income introduction.

Ao longo da história, diversas foram as tentativas da ciência em sistematizar o conhecimento sobre as cidades. Um conjunto de recentes descobertas empíricas deu início a uma nova ciência urbana, fundamentada nos sistemas complexos( BATTY , 2013). Uma das raízes empíricos dessa ciência está nas análises de escalamento entre diversas variáveis urbanas com a população das cidades. Como hipótese fundamental, propõe-se que por mais diferentes que sejam, parece existir um padrão muito claro de escalamento entre a população dos centros urbanos com variáveis de produção socioeconômica (superlinear) e variáveis infraestruturais (sublinear). Um modelo de campo médio proposto por Bettencourt( BETTENCOURT , 2013) parece apresentar uma prossível explicação para a origem dessas leis de escala nas interações sociais. Essa hipótese ainda carece, entretanto, de maiores comprovações empíricas e de maiores explorações do modelo proposto. O presente trabalho apresenta os resultados de uma exploração das leis de escala entre as cidades brasileiras e uma tradução do modelo de Bettencourt em uma estrutura de modelagem por agentes. Os padrões de escalamento das cidades brasileiras parecem seguir aqueles encontrados em outras cidades do mundo com certa robustez. Escalamentos de variáveis de arrecadação e de despesas foram estudados e as cidades brasileiras parecem otimizá-los a medida que crescem. O modelo se mostrou coerente com os fatos observados empiricamente e indicou que cidades muito desiguais tendem a ter menores produções socioeconômicas e que áreas de interações maiores e custos de transporte menores tendem a produzir mais interações socioeconômicas / Throughout history science has tried in many ways to sistematyze the knowledge about cities. Recent empirical discoveries started a new urban science, based on complex systems and data science( BATTY , 2013). One of the empirical foundation of this science is the scaling laws of diferent urban variables in relation to the urban population size. As a main hypothesis, it is sugested that as diferent as cities may be, there seems to be an evident scaling pattern between population size and socioeconomic production (superlinear) and infrastrufture variables (sublinear). A mean field model proposed by Bettencourt( BETTENCOURT , 2013) appears to present a plausible explanation for the origin of scaling laws in social interactions. However, this hypothesis still lacks more concluding empirical proof and further study of the model itself. This paper presents the results of an exploration of the scaling laws among Brazilian cities and a translation of Bettencourts model in a ABM framework. The scaling patterns of Brazilian cities appear to follow those found in other cities in the world with a certain robustness. Tax revenues and costs scaling were studied and Brazilian cities seem to optimize them as they grow. The model proved to be consistent with the facts observed empirically and indicated that very unequal city tend to have lower socioeconomic productions and greater areas of interactions and lower transportation costs tends to imply greater socioeconomic productions

Dans cette thèse nous étudions le rôle de la motivation intrinsèque dans l’émergence et le développement des systèmes communicationnels. Notre objectif est d’explorer comment des populations d’agents artificiels peuvent utiliser un système de motivation computationnel particulier, appelé l’autotelic principle, pour réguler leur développement linguistique et les dynamiques qui en résultent au niveau de la population.Nous proposons d’abord une mise en œuvre concrète de l’autotelic principle. Le noyau de ce système repose sur l’équilibre des défis, des tâches à accomplir afin d’atteindre un objectif, et des compétences, les capacités que le système peut utiliser pour accomplir les différentes tâches. La relation entre les deux éléments n’est pas stable mais se déstabilise régulièrement lorsque de nouvelles compétences sont acquises, ce qui permet au système de tenter des défis de plus grande complexité. Ensuite, nous testons l’utilité de ce système de motivation dans une série d’expériences sur l’évolution du langage. Dans le premier ensemble d’expériences, une population d’agents artificiels doit développer une langue pour se référer à des objets ayant des caractéristiques discrètes. Ces expériences se concentrent sur la façon dont les systèmes communicatifs non ambigus peuvent émerger lorsque l’autotelic principle est utilisé pour réguler le développement du langage en étapes de difficulté croissante. Dans le deuxième ensemble d’expériences, les agents doivent créer un langage artificiel pour communiquer sur des couleurs. Dans cette partie, on explore comment le système de motivation peut contrôler la complexité linguistique des interactions pour un domaine continu et on examine aussi la validité de l’autotelic principle en tant que mécanisme permettant de réguler simultanément plusieurs stratégies linguistiques de difficulté similaire. En résumé, nous avons démontré à travers de notre travail que l’autotelic principle peut être utilisé comme un mécanisme général pour réguler la complexité du langage développé de manière autonome en domaines discrets et continus. / This thesis studies the role of intrinsic motivation in the emergence and development of communicative systems in populations of artificial agents. To be more specific, our goal is to explore how populations of agents can use a particular motivation system called autotelic principle to regulate their language development and the resulting dynamics at the population level.To achieve this, we first propose a concrete implementation of the autotelic principle. The core of this system is based on the balance between challenges, tasks to be done to achieve a goal, and skills, the abilities the system can employ to accomplish the different tasks. The relation between the two elements is not steady but regularly becomes destabilised when new skills are learned, which allows the system to attempt challenges of increasing complexity. Then, we test the usefulness of the autotelic principle in a series of language evolution experiments. In the first set of experiments, a population of artificial agents should develop a language to refer to objects with discrete values. These experiments focus on how unambiguous communicative systems can emerge when the autotelic principle is employed to scaffold language development into stages of increasing difficulty. In the second set of experiments, agents should agree on a language to communicate with about colour samples. In this part, we explore how the motivation system can regulate the linguistic complexity of interactions for a continuous domain and examine the value of the autotelic principle as a mechanism to control several language strategies simultaneously. To summarise, we have shown through our work that the autotelic principle can be used as a general mechanism to regulate complexity in language emergence in an autonomous way for discrete and continuous domains.

Ao longo da história, diversas foram as tentativas da ciência em sistematizar o conhecimento sobre as cidades. Um conjunto de recentes descobertas empíricas deu início a uma nova ciência urbana, fundamentada nos sistemas complexos( BATTY , 2013). Uma das raízes empíricos dessa ciência está nas análises de escalamento entre diversas variáveis urbanas com a população das cidades. Como hipótese fundamental, propõe-se que por mais diferentes que sejam, parece existir um padrão muito claro de escalamento entre a população dos centros urbanos com variáveis de produção socioeconômica (superlinear) e variáveis infraestruturais (sublinear). Um modelo de campo médio proposto por Bettencourt( BETTENCOURT , 2013) parece apresentar uma prossível explicação para a origem dessas leis de escala nas interações sociais. Essa hipótese ainda carece, entretanto, de maiores comprovações empíricas e de maiores explorações do modelo proposto. O presente trabalho apresenta os resultados de uma exploração das leis de escala entre as cidades brasileiras e uma tradução do modelo de Bettencourt em uma estrutura de modelagem por agentes. Os padrões de escalamento das cidades brasileiras parecem seguir aqueles encontrados em outras cidades do mundo com certa robustez. Escalamentos de variáveis de arrecadação e de despesas foram estudados e as cidades brasileiras parecem otimizá-los a medida que crescem. O modelo se mostrou coerente com os fatos observados empiricamente e indicou que cidades muito desiguais tendem a ter menores produções socioeconômicas e que áreas de interações maiores e custos de transporte menores tendem a produzir mais interações socioeconômicas / Throughout history science has tried in many ways to sistematyze the knowledge about cities. Recent empirical discoveries started a new urban science, based on complex systems and data science( BATTY , 2013). One of the empirical foundation of this science is the scaling laws of diferent urban variables in relation to the urban population size. As a main hypothesis, it is sugested that as diferent as cities may be, there seems to be an evident scaling pattern between population size and socioeconomic production (superlinear) and infrastrufture variables (sublinear). A mean field model proposed by Bettencourt( BETTENCOURT , 2013) appears to present a plausible explanation for the origin of scaling laws in social interactions. However, this hypothesis still lacks more concluding empirical proof and further study of the model itself. This paper presents the results of an exploration of the scaling laws among Brazilian cities and a translation of Bettencourts model in a ABM framework. The scaling patterns of Brazilian cities appear to follow those found in other cities in the world with a certain robustness. Tax revenues and costs scaling were studied and Brazilian cities seem to optimize them as they grow. The model proved to be consistent with the facts observed empirically and indicated that very unequal city tend to have lower socioeconomic productions and greater areas of interactions and lower transportation costs tends to imply greater socioeconomic productions

During the 1990s, artists started to explore the possibilities of the World Wide Web. This thesis investigates online artworks by studying their agency. Why do people interact with them, as if they are alive? How do they mobilise people, or make them share visions and ideas? Based on research in largely untapped archives, it presents an in-depth examination of several case studies, exploring the artwork's ability to have the power to act in a variety of social settings. Through studying the life trajectory of the artwork, it also offers insights in how these dynamic entities undergo changes over time and across cultures. Grounded in theoretical literature on the agency of art, this research offers an innovative way of understanding Internet art and it contributes to wider conversations about the agency of art and artefacts. Case studies include: Mouchette (Martine Neddam), 'Mouchette' (1996-present). Web project (www.mouchette.org). Collection of Stedelijk Museum (Amsterdam). Shu Lea Cheang, 'Brandon' (1998-1999). Web project (brandon.guggenheim.org). Collection of Solomon R. Guggenheim Museum (New York). Lynn Hershman Leeson, 'Agent Ruby' (1998-2002). Web project (agentruby.sfmoma.org). Collection of SFMOMA (San Francisco).

Depuis de nombreuses années, nous nous sommes efforcés de comprendre le comportement humain et nos interactions avec l'environnement sociotechnique. Grâce à l'avancée de nos connaissances dans ce domaine, nous avons contribué à la conception de technologies et de processus de travail nouveaux ou améliorés. Historiquement, une part importante du travail d'analyse des interactions sociales fut entreprise au sein des sciences sociales. Cependant, la simulation informatique a apporté un nouvel outil pour tenter de comprendre et de modéliser les comportements humains. En utilisant une approche à base d'agents, cette présentation décrit mon travail sur la construction de modèles informatiques du comportement humain pour guider la conception par la simulation. A l'aide d'exemples issus de projets des deux domaines d'application que sont la gestion des crises et de l'urgence et la gestion de l'énergie, je décris comment mon travail aborde certains problèmes centraux à la simulation sociale à base d'agents. Le premier concerne le processus par lequel nous développons ces modèles. Le second problème provient de la nature des systèmes sociotechniques. Les sociétés humaines constituent un exemple parfait de système complexe possédant des caractéristiques d'auto-organisation et d'adaptabilité, et affichant des phénomènes émergents tels que la coopération et la robustesse. Je décris comment la théorie des systèmes complexes peut être appliquée pour améliorer notre compréhension des systèmes sociotechniques, et comment nos interactions au niveau microscopique mènent à l'émergence d'une conscience mutuelle pour la résolution de problèmes. A partir de systèmes de simulation à base d'agents, je montre comment la conscience du contexte peut être modélisée. En terme de perspectives, j'expliquerai comment la hausse de la prévalence des agents artificiels dans notre société nous forcera à considérer de nouveaux types d'interactions et de comportements coopératifs.

Animal groups often exhibit highly coordinated collective motion in a variety of situations. For example, bird flocks, schools of fish, a flock of sheep being herded by a dog and highly efficient traffic on an ant trail. Although these phenomena can be observed every day all over the world our knowledge of what rules the individual's in such groups use is very limited. Questions of this type has been studied using so called self-propelled particle (SPP) models, most of which assume that collective motion arises from individuals aligning with their neighbors. Here we introduce and analyze a SPP-model based on attraction alone. We find that it produces all the typical groups seen in alignment-based models and some novel ones. In particular, a group that exhibits collective motion coupled with non-trivial internal dynamics. Groups that have this property are rarely seen in SPP-models and we show that even when a repulsion term is added to the attraction only model such groups are still present. These findings suggest that an interplay between attraction and repulsion may be the main driving force in real flocks and that the alignment rule may be superfluous. We then proceed to model two different experiments using the SPP-model approach. The first is a shepherding algorithm constructed primarily to model experiments where a sheepdog is herding a flock of sheep. We find that in addition to modeling the specific experimental situation well the algorithm has some properties which may make it useful in more general shepherding situations. The second is a traffic model for leaf-cutting ants bridges. Based on earlier experiments a set of traffic rules for ants on a very narrow bridge had been suggested. We show that these are sufficient to produce the observed traffic dynamics on the narrow bridge. And that when extended to a wider bridge by replacing 'Stop' with 'Turn' the new rules are sufficient to produce several key characteristics of the dynamics on the wide bridge, in particular three-lane formation.

Manufacturing industry is under permanent pressure to maintain its economic growth and profitability as strong societal backbone. At the same time pressures of waste generation and resource consumption are increasing as result of manufacturing operations. Since manufacturing industry is one of the major consumers of natural resources it is therefore essential to reduce dependency on natural resources by decoupling economic growth from consumption. Resource efficiency approaches can improve the performance of production systems by reducing resource losses. However, the fundamental assumption at the basis of resource efficiency approaches is that resources are available infinitely. As a consequence, challenges of sustainability and resource scarcity remain inadequately addressed. The objective of this research is to develop analysis methods and decision support tools for manufacturing industry to facilitate its transition from linear production systems to circular manufacturing systems, which are economically viable and environmentally sustainable. The initial scope of study focuses on industrial resource efficiency assessment in production systems. Expanding the view to a manufacturing system perspective, the current research is explored with regard to circular manufacturing systems in the context of economic benefits, resource scarcity and waste generation. Systematic analysis methods and decision support tools are developed for industrial companies to facilitate the adaption of circular manufacturing systems. These developments are supported by industrial case studies. The analysis methods are to the largest extent based on agent-based simulation approaches. The tools are capable of assessing the economic and environmental impact of different business models, design strategies as well as supply chains settings. Moreover, the tools are able to determine whether introductions of new (circular) business models will be adopted by customers. One empirical market study is performed to investigate value propositions of a circular business approaches based on customer decisions. / <p>QC 20170825</p>