Through social learning, animals acquire information from others, such as skills and knowledge about the environment. High fidelity transmission of locally adaptive information can lead to population-specific traits, or cultural traits, which are fundamental to the emergence of culture. Despite social learning being widespread in the animal kingdom, culture is rare in nature. This thesis investigates the evolution, ecology, and dynamics of social learning, to increase our understanding why species differ in their ability to generate and accumulate cultural traits, and ultimately how complex human culture emerged. Chapter 2 introduces a novel computational model that explicitly incorporates competition into the social learning context. The model predicts that social learning is most adaptive where resources are unevenly distributed and stable through time, even if individuals compete for limited resources. The model provides an explanation for reports of animals disregarding social information, even if it is available. Testing these predictions Chapter 3 presents a bumblebee foraging experiment. The results support the theoretical predictions, showing that foragers use social information to find rewarding flowers, even if social cues indicate competition. Chapter 4 further examines the trade-off between access to social information and competition. Individuals that are central in a learning network have more opportunities to acquire information from others, but also face an increased likelihood to engage in competition. The results of this model suggest that across different learning contexts centrality is only beneficial for dominant individuals because dominance can mitigate the effect of competition. This also shows that individual phenotypic differences affect the utility of social information. Chapter 5 uses a dynamic network model approach to tests whether these differences modulate the structure of learning networks and by extension of the population. The model shows that this is the case and that where social learning is favoured by the environment networks are more structured. Chapter 6, studies the drivers behind individual differences in social learning. The chapter focusses on reports of sex differences in social information use and finds that they can be explained by differences in risk taking behaviour. The results highlight the importance of the feedback between learning individuals, and how this shapes social learning dynamics on an individual as well as on a population level.

abstract: Free/Libre Open Source Software (FLOSS) is the product of volunteers collaborating to build software in an open, public manner. The large number of FLOSS projects, combined with the data that is inherently archived with this online process, make studying this phenomenon attractive. Some FLOSS projects are very functional, well-known, and successful, such as Linux, the Apache Web Server, and Firefox. However, for every successful FLOSS project there are 100's of projects that are unsuccessful. These projects fail to attract sufficient interest from developers and users and become inactive or abandoned before useful functionality is achieved. The goal of this research is to better understand the open source development process and gain insight into why some FLOSS projects succeed while others fail. This dissertation presents an agent-based model of the FLOSS development process. The model is built around the concept that projects must manage to attract contributions from a limited pool of participants in order to progress. In the model developer and user agents select from a landscape of competing FLOSS projects based on perceived utility. Via the selections that are made and subsequent contributions, some projects are propelled to success while others remain stagnant and inactive. Findings from a diverse set of empirical studies of FLOSS projects are used to formulate the model, which is then calibrated on empirical data from multiple sources of public FLOSS data. The model is able to reproduce key characteristics observed in the FLOSS domain and is capable of making accurate predictions. The model is used to gain a better understanding of the FLOSS development process, including what it means for FLOSS projects to be successful and what conditions increase the probability of project success. It is shown that FLOSS is a producer-driven process, and project factors that are important for developers selecting projects are identified. In addition, it is shown that projects are sensitive to when core developers make contributions, and the exhibited bandwagon effects mean that some projects will be successful regardless of competing projects. Recommendations for improving software engineering in general based on the positive characteristics of FLOSS are also presented. / Dissertation/Thesis / Ph.D. Computer Science 2011

O fenômeno do congestionamento, decorrente do rápido aumento da demanda por todos os meios de transporte só tende a se agravar, já que sistemas de transporte (vistos como um todo) têm um grande impacto na economia mundial. No caso do transporte veicular em particular, é notório que a demanda por mobilidade é uma das características da nossa sociedade. O impacto direto e indireto dos congestionamentos em áreas urbanas e interurbanas é imenso, e precisam ser avaliados adequadamente para que seus efeitos sejam pelo menos minorados. Esta dissertação apresenta o AVNET, uma modelagem baseada em agentes para avali- ação do balanceamento de carga em redes de tráfego veicular, capaz de investigar micros- copicamente a interação entre oferta, demanda e as particularidades do comportamento dos motoristas, aqui tratados como agentes autônomos capazes de perceber o estado do ambiente e se adaptar a ele utilizando replanejamento heurístico. O principal objetivo do AVNET é investigar a interação entre a percepção que o agente possui do tráfego e a consequente adaptação através da mudança de rota durante a viagem. De forma cíclica, o AVNET propõe que o estado do ambiente influencia na percepção do agente, e a ação do agente influencia no estado do ambiente. As medidas de balanceamento de carga visam avaliar o desempenho do ponto de vista do motorista, ao invés de abordar a avaliação do ponto de vista da rede como algumas abordagens tradicionalmente propõe. Experimentos foram realizados a partir da variação nas condições de oferta - utili- zando uma rede com topologia em estilo de grade e uma abstração de algumas vias arte- riais da cidade de Porto Alegre/RS - variação nas condições de demanda - o tipo de dis- tribuição e número de viagens - e dos tipos de agentes utilizados. Os resultados ajudam a responder como será o balanceamento de carga de redes de tráfego veicular conforme as condições de oferta e demanda do ambiente, e de percepção/ação dos agentes. / The phenomenon of congestion, due to the rapid increase in demand for all means of transport is only going to worsen, since systems transport (seen as a whole) have a major impact on the world economy. In the case of vehicular transport in particular, it is clear that the demand for mobility is a characteristic of our society. The direct and indirect impact of congestion in urban and long distance is immense, and must be properly evaluated for their effects are at least mitigated. This dissertation presents the AVNET, an agent-basead modelling to evaluate load bal- ancing in networks of vehicular traffic, able to microscopically investigate the interaction between supply, demand and the peculiarities of the behavior of drivers, here treated as autonomous agents, capable to perceive the state of the environment and adapt to it using heuristic redesign. The main goal of AVNET is to investigate the interaction between the perception that the agent has the traffic and the consequent adaptation by changing the route during the trip. Cyclically, the AVNET propose that the state of the environment influences the perception of the agent and the agent’s action influences the state of the environment. Experiments were performed from the variation in supply conditions - using a network grid topology and an abstraction of some arterial roads in the city of Porto Alegre/RS - changes in demand conditions - the type of distribution and number of trips - and the types of agents used. The results will help answer how the balancing network load of vehicular traffic as conditions of supply and demand of the environment, and perception / action agents.

O fenômeno do congestionamento, decorrente do rápido aumento da demanda por todos os meios de transporte só tende a se agravar, já que sistemas de transporte (vistos como um todo) têm um grande impacto na economia mundial. No caso do transporte veicular em particular, é notório que a demanda por mobilidade é uma das características da nossa sociedade. O impacto direto e indireto dos congestionamentos em áreas urbanas e interurbanas é imenso, e precisam ser avaliados adequadamente para que seus efeitos sejam pelo menos minorados. Esta dissertação apresenta o AVNET, uma modelagem baseada em agentes para avali- ação do balanceamento de carga em redes de tráfego veicular, capaz de investigar micros- copicamente a interação entre oferta, demanda e as particularidades do comportamento dos motoristas, aqui tratados como agentes autônomos capazes de perceber o estado do ambiente e se adaptar a ele utilizando replanejamento heurístico. O principal objetivo do AVNET é investigar a interação entre a percepção que o agente possui do tráfego e a consequente adaptação através da mudança de rota durante a viagem. De forma cíclica, o AVNET propõe que o estado do ambiente influencia na percepção do agente, e a ação do agente influencia no estado do ambiente. As medidas de balanceamento de carga visam avaliar o desempenho do ponto de vista do motorista, ao invés de abordar a avaliação do ponto de vista da rede como algumas abordagens tradicionalmente propõe. Experimentos foram realizados a partir da variação nas condições de oferta - utili- zando uma rede com topologia em estilo de grade e uma abstração de algumas vias arte- riais da cidade de Porto Alegre/RS - variação nas condições de demanda - o tipo de dis- tribuição e número de viagens - e dos tipos de agentes utilizados. Os resultados ajudam a responder como será o balanceamento de carga de redes de tráfego veicular conforme as condições de oferta e demanda do ambiente, e de percepção/ação dos agentes. / The phenomenon of congestion, due to the rapid increase in demand for all means of transport is only going to worsen, since systems transport (seen as a whole) have a major impact on the world economy. In the case of vehicular transport in particular, it is clear that the demand for mobility is a characteristic of our society. The direct and indirect impact of congestion in urban and long distance is immense, and must be properly evaluated for their effects are at least mitigated. This dissertation presents the AVNET, an agent-basead modelling to evaluate load bal- ancing in networks of vehicular traffic, able to microscopically investigate the interaction between supply, demand and the peculiarities of the behavior of drivers, here treated as autonomous agents, capable to perceive the state of the environment and adapt to it using heuristic redesign. The main goal of AVNET is to investigate the interaction between the perception that the agent has the traffic and the consequent adaptation by changing the route during the trip. Cyclically, the AVNET propose that the state of the environment influences the perception of the agent and the agent’s action influences the state of the environment. Experiments were performed from the variation in supply conditions - using a network grid topology and an abstraction of some arterial roads in the city of Porto Alegre/RS - changes in demand conditions - the type of distribution and number of trips - and the types of agents used. The results will help answer how the balancing network load of vehicular traffic as conditions of supply and demand of the environment, and perception / action agents.

O fenômeno do congestionamento, decorrente do rápido aumento da demanda por todos os meios de transporte só tende a se agravar, já que sistemas de transporte (vistos como um todo) têm um grande impacto na economia mundial. No caso do transporte veicular em particular, é notório que a demanda por mobilidade é uma das características da nossa sociedade. O impacto direto e indireto dos congestionamentos em áreas urbanas e interurbanas é imenso, e precisam ser avaliados adequadamente para que seus efeitos sejam pelo menos minorados. Esta dissertação apresenta o AVNET, uma modelagem baseada em agentes para avali- ação do balanceamento de carga em redes de tráfego veicular, capaz de investigar micros- copicamente a interação entre oferta, demanda e as particularidades do comportamento dos motoristas, aqui tratados como agentes autônomos capazes de perceber o estado do ambiente e se adaptar a ele utilizando replanejamento heurístico. O principal objetivo do AVNET é investigar a interação entre a percepção que o agente possui do tráfego e a consequente adaptação através da mudança de rota durante a viagem. De forma cíclica, o AVNET propõe que o estado do ambiente influencia na percepção do agente, e a ação do agente influencia no estado do ambiente. As medidas de balanceamento de carga visam avaliar o desempenho do ponto de vista do motorista, ao invés de abordar a avaliação do ponto de vista da rede como algumas abordagens tradicionalmente propõe. Experimentos foram realizados a partir da variação nas condições de oferta - utili- zando uma rede com topologia em estilo de grade e uma abstração de algumas vias arte- riais da cidade de Porto Alegre/RS - variação nas condições de demanda - o tipo de dis- tribuição e número de viagens - e dos tipos de agentes utilizados. Os resultados ajudam a responder como será o balanceamento de carga de redes de tráfego veicular conforme as condições de oferta e demanda do ambiente, e de percepção/ação dos agentes. / The phenomenon of congestion, due to the rapid increase in demand for all means of transport is only going to worsen, since systems transport (seen as a whole) have a major impact on the world economy. In the case of vehicular transport in particular, it is clear that the demand for mobility is a characteristic of our society. The direct and indirect impact of congestion in urban and long distance is immense, and must be properly evaluated for their effects are at least mitigated. This dissertation presents the AVNET, an agent-basead modelling to evaluate load bal- ancing in networks of vehicular traffic, able to microscopically investigate the interaction between supply, demand and the peculiarities of the behavior of drivers, here treated as autonomous agents, capable to perceive the state of the environment and adapt to it using heuristic redesign. The main goal of AVNET is to investigate the interaction between the perception that the agent has the traffic and the consequent adaptation by changing the route during the trip. Cyclically, the AVNET propose that the state of the environment influences the perception of the agent and the agent’s action influences the state of the environment. Experiments were performed from the variation in supply conditions - using a network grid topology and an abstraction of some arterial roads in the city of Porto Alegre/RS - changes in demand conditions - the type of distribution and number of trips - and the types of agents used. The results will help answer how the balancing network load of vehicular traffic as conditions of supply and demand of the environment, and perception / action agents.

No description available.

Organizations, once established, tend not to change, typically going obsolete as society continues to evolve. This makes adaptability an important issue. Organizational members must make sense to each other, or coordination suffers. They must also make sense to environmental actors, or the organization will not achieve the support it needs to survive. This sense-making is a process of institutionalization, of constructing a shared understanding of the organization's enterprise, business and environment. When environmental actors adopt new priorities, ideas and modes of thinking, organizations must develop a new understanding of reality or go obsolete. To stay adaptable, organizations needs to contain competing perspectives. But the pressures to conform and to coordinate make it difficult for established organizations to adapt, trapped by the very benefits of increased efficiency. Using an agent-based model of organizational institutionalization, I show that an organization's adaptability is highly dependent on structural elements that affect the member interaction frequencies, and that organizations that leverage the strength of weak ties between member groups can maintain adaptability. The effects of changes to any of these elements are decidedly non-linear, however, which helps explain why it is difficult to design effective organizations. Organizational structure is one part of a tri-partite framework of institutional development in organizations and of organizational adaptability, where the other two parts are the individual characteristics of the members and the content of the organizational culture.

Un système logistique est une composante essentielle d'un système spatial dans lequel les acteurs s'organisent autour d'infrastructures pour faire circuler des flux (de marchandises, d'information et financier) sur un territoire. L'organisation logistique globale résulte d'un processus auto-organisé et distribué de la part des acteurs. Ce travail vise à comprendre, à de multiples échelles, comment des acteurs autonomes et très hétérogènes (dans leurs modes de fonctionnements et dans leurs objectifs), s'organisent collectivement autour des infrastructures à leurs dispositions pour gérer des flux soumis à un ensemble de contraintes (temporelles, spatiales,...). On propose ici un modèle orienté agent permettant de simuler les processus de création et d'organisation des flux liés à la logistique sur un territoire. Le modèle prévoit de décrire l'interface entre les flux internationaux et les flux urbains afin de comprendre comment les dynamiques portuaires et urbaines cohabitent au sein du système. Le modèle intègre une dynamique structurelle et organisationnelle grâce aux graphes dynamiques afin de représenter l'évolution du système. Le modèle permet ainsi aux agents de s'adapter, comme dans la réalité, à des perturbations du système. / A logistic system is an essential component of a spatial system. Actors are organised around infrastructures in order to move different kinds of flow (of goods, of information, or financial) over a territory. The logistic organisation comes from an auto-organised and distributed process from the actors. This works aims to understand, at different scales, how autonomous and heterogeneous actors (according to their goals and methods to take decisions) are collectively organised around infrastructures to manage different kinds of flow, and despite numerous constraints (temporal, spatial,...). We propose an agent-based model which allows to simulate the processes to create and organise logistic flow over a territory. The model describes an interface between international and urban flow in order to understand how the port and urban dynamics work together. The model integrates a structural and organisational dynamics thanks to dynamic graphs in order to represent the evolution of this kind of system. Thus, the agents can adapt themselves to system's perturbations as in the reality.

Cancer is a complex illness that affects millions of people every year. Amongst the most frequently encountered variants of this illness are solid tumours. The growth of solid tumours depends on a large number of factors such as oxygen concentration, cell reproduction, cell movement, cell death, and vascular environment. The aim of this thesis is to provide further insight in the interconnections between these factors by means of numerical simulations. We present a multiscale model for tumor growth by coupling a microscopic, agent-based model for normal and tumor cells with macroscopic mean-field models for oxygen and extracellular concentrations. We assume the cell movement to be dominated by Brownian motion. The temporal and spatial evolution of the oxygen concentration is governed by a reaction-diffusion equation that mimics a balance law.To complement this macroscopic oxygen evolution with microscopic information, we propose a lattice-free approach that extends the vascular distribution of oxygen. We employ a Markov chain to estimate the sprout probability of new vessels. The extension of the new vessels is modeled by enhancing the agent-based cell model with chemotactic sensitivity. Our results include finite-volume discretizations of the resulting partial differential equations and suitable approaches to approximate the stochastic differential equations governing the agent-based motion. We provide a simulation framework that evaluates the effect of the various parameters on, for instance, the spread of oxygen. We also show results of numerical experiments where we allow new vessels to sprout, i.e. we explore angiogenesis. In the case of a static vasculature, we simulate the full multiscale model using a coupled stochastic/deterministic discretization approach which is able to reduce variance at least for a chosen computable indicator, leading to improved efficiency and a potential increased reliability on models of this type.

The question how a least-cost spatial allocation of sustainable electricity infrastructure may look like using different decision-making procedures (markets, different kinds of land-use and grid regulations) has not yet been analysed explicitly. We measure the sustainability of emerging energy landscapes providing power from renewable energy sources (RES) by an overall welfare function also comprising all kinds of space-related disutilities, i.e. spatial externalities - be they site-specific or related to the distance to a residential area (consumer centre). The presented agent-based model (ABM) concept aims at assessing different policy scenarios to govern the land-use for energetic purposes under the constraint of ensuring the electricity supply for a virtual landscape with RES. To derive optimal spatial allocation an agent-based modelling approach is implemented, which includes a virtual landscape, three settlements as demand centres and profit-oriented producers of renewable power. For the design of the electricity grid and the calculation of grid-related reinforcement costs a load-flow model is applied, being also able to map grid externalities during the RES expansion in space. The model allows RES producers to choose profit-maximising cells for plant installations until the given demand for power of the virtual landscape is met. Different policy scenarios allocate particular costs to agents (e.g. grid reinforcement costs, spatial externalities) or restrict the land-use with respect to ecological or social restraints. Furthermore, consumer centres have the possibility to follow own particular regional strategies, to increase their individual benefit. The overall efficiency of allocation (total cost level) as well as the distributional fairness (regional net costs) are evaluated for the policy scenarios and the regional strategies.