Die Arbeit beschreibt ein Modell, dass den Materialfluss in Transport- und Puffersystemen mit Hilfe eines agenten-basierten Ansatzes realistisch abbildet. Auf der Basis von Produktionsprogrammen werden individuelle Güter in beliebigen Netzwerkstrukturen mit Hilfe direkter und indirekter Interaktionen behinderungsvermeidend gesteuert. / The thesis describes a model that realistically illustrates the material flow in transport and buffer systems by means of an agent-based approach. Individual goods are steered hindrance-avoiding in arbitrary network structures based on production programs by means of direct and indirect interactions.

Choisir un partenaire sexuel est une décision importante pour un animal. Parce que cette décision va considérablement affecter son succès reproducteur, l’individu doit se baser sur un ensemble de traits qui reflètent la qualité du partenaire. Depuis peu, une attention particulière est portée sur l’importance de la cognition dans le contexte de choix de partenaire. En effet, la capacité à percevoir, intégrer, mémoriser et utiliser l’information disponible dans l’environnement permet aux individus de répondre de manière appropriée aux problèmes qu’ils rencontrent et d’ajuster leur comportement en conséquent. Si les femelles retirent un bénéfice à s’apparier avec des mâles capables de répondre aux changements de leur environnement, ces derniers pourraient avoir un accès privilégié à l’appariement lors du choix de partenaire des femelles. Certaines évidences appuient cette idée en démontrant notamment des relations positives entre les capacités cognitives des mâles et leur succès d’appariement et reproducteur et en révélant des préférences sexuelles femelles pour des traits cognitifs mâles. Cependant, ces résultats restent très contrastés, particulièrement chez les animaux non humains où l’importance du choix de partenaire dans l’évolution de la cognition n’est pas encore clairement définie. L’objectif de ma thèse était donc d’explorer le rôle du choix de partenaire dans l’évolution de la cognition mâle et femelle en combinant l’approche observationnelle sur une espèce d’oiseaux monogame et l’approche théorique en utilisant un modèle à base d’agents. Plus précisément, en réalisant des expériences en laboratoire sur le Diamant mandarin (Taeniopygia guttata), j’ai notamment testé si les femelles démontrent une préférence pour des mâles capables d’ajuster leur comportement d’approvisionnement en réponse à un changement environnemental. J’ai ensuite examiné, dépendamment de leurs propres capacités cognitives, si les femelles expriment des préférences pour des mâles performants dans quatre tests psychométriques différents. J’ai finalement exploré les rôles respectifs de la sélection naturelle et intersexuelle en simulant l’évolution de la cognition sous différents scénarios environnementaux. Les résultats de cette thèse ont révélé que les femelles diamants mandarin exprimaient une préférence pour les mâles capables d’ajuster leur comportement d’approvisionnement ainsi que les mâles performants dans certaines tâches cognitives. Cependant, ces préférences n’étaient pas unanimes et dépendaient des propres capacités cognitives des femelles à performer dans ces différentes situations. À l’échelle évolutive, la sélection intersexuelle à travers le choix de partenaire modifiait les patrons d’évolution de la cognition prédits lorsque la sélection naturelle opérait seule. En effet, elle favorisait l’évolution de bonnes capacités cognitives lorsque les contraintes environnementales étaient faibles, mais maintenait de la diversité cognitive lorsque ces contraintes étaient élevées. Dans l’ensemble, ces résultats suggèrent que le choix de partenaire jouerait un rôle important dans l’évolution et le maintien de diversité cognitive au sein des populations. Néanmoins, les conséquences évolutives du choix de partenaire sur les capacités cognitives des individus dépendraient de l’avantage adaptatif à s’apparier avec un mâle plus performant, c’est-à-dire de la capacité cognitive mâle considérée, des caractéristiques des femelles et de l’environnement dans lequel ce choix est fait. / Choosing a mate is an important decision for an animal. Because this decision significantly affects an individual’s reproductive success, it must base its choice according to different traits that reflect the quality of potential mates. Recently, a particular attention has been given to cognitive traits in mate choice context. Indeed, the ability to perceive, integrate, memorize and use the information available in the environment allows individuals to act properly when facing a problem and to adjust their behaviours accordingly. Given that females could benefit from choosing males capable of responding to environmental changes, those with good cognitive abilities should have privileged access to females in mate choice contexts. Some evidence supports this idea by revealing positive relationships between males’ cognitive abilities and their mating and reproductive success as well as female mating preference for male cognitive abilities. However, these results stay contrasted, particularly in non-human animals for which the importance of mate choice in the evolution of cognition is still not clearly defined. The objective of my PhD was to explore the role of mate choice in the evolution of male and female cognition by combining an observational approach using a monogamous bird species and a theoretical approach using an agent-based model. Specifically, by running laboratory experiments on zebra finches (Taeniopygia guttata), I tested whether females demonstrated a mate preference for males able to adjust their foraging behaviour following an environmental change. Then, I investigated whether females, depending on their own cognitive abilities, demonstrated a mate preference for better performers in four different psychometric tests. I finally explored the relative role of natural and sexual selection by simulating the evolution of cognition under different environmental scenarios. The results of this PhD project revealed that zebra finch females preferred males exhibiting greater behavioural plasticity in their foraging tactic use as well as males performing better in several cognitive tasks. However, females’ preference for cognitive abilities was not unanimous but depended on females’ own abilities to perform in these tasks. At the evolutionary scale, intersexual selection through mate choice changed the evolutive patterns observed under natural selection alone. In fact, intersexual selection promoted good cognitive abilities under most favourable environments but maintained cognitive diversity under the harsher ones. Taken together, these results suggest that mate choice plays an important role in the evolution and maintenance of cognitive diversity within populations. Nevertheless, the evolutive consequences of mate choice on individual cognitive abilities should depend on i) the adaptive value of mating with a male with better performance, and thus, on the cognitive ability considered, ii) the female characteristics and iii) the local environment during mate choice.

In this thesis, the central interest is to better understand how participatory methods applied during participatory processes in natural resources management can serve as nuclei for social learning. Thereby, the main focus is on learning via interaction in groups. My approach begins with the aim of developing an analytical framework which reflects the main processes that are effective within participatory methods. The framework presents an analytical tool, including proposed methods to monitor and compare the results of participatory approaches with respect to social learning. Building upon this framework, I develop an agent-based model to simulate and explore group dynamics. This model is intended to support a theoretical exploration of whether or not and if so, at what stage, personal views of a problem evolve into a shared understanding of a problem (which can be seen as a key element of social learning), and an assessment of how individual mental models and group properties relate to each other. Results of the model are interpreted to offer suggestions about factors hindering or fostering social learning during the application of participatory methods.

Les prairies de montagne offrent de nombreux services ecosystémiques qui sont menacés par le changement global. Les traits fonctionnels constituent un outil prometteur pour caractériser les réponses des communautés à des changements de conditions environnementales et leurs répercussions sur les services associés. Cependant, des résulats de plus en plus nombreuses soulignent l’importance de la variabilité intra-spécifique des traits a également été mise en évidence. Pour étudier ces effets, je propose un nouveau modèle à base d’agents, MountGrass, qui combine la modélisation de communautés végétales riches en espèces avec des processus de plasticité phénotypique. Ces deux éléments au coeur du modèle sont associés grâce à des compromis d’allocation basés sur des patrons empiriques établis de stratégies d’utilisation des resources.Avec MountGrass, j’ai exploré l’impact de la plasticité phénotypique sur la croissance individuelle et les propriétés principales des communautés prairiales. À l’échelle individuelle, le modèle paramétré a révélé un fort impact positif de la plasticité phénotypique sur la croissance mais aussi sur la niche fondamentaledes espèces. Des phénomènes de convergence et de réduction de la sensibilité aux variations de conditionsexpliquent ces effets. À l’échelle des communautés, les simulations ont confirmé de forts effets de la plasticité sur la structure des communautés et leur diversité spécifique. Ces effets sont expliqués par l’effet combiné de la réduction du filtre abiotique et de la réduction des différences de compétitivité. Cependant, aucun effet majeur sur la stratégie dominante ou la productivité n’a pu être mis en évidence.Des implémentations alternatives ou des extensions du modèle devraient permettre de tester la robustesse des résultats obtenus et d’analyser d’autres schémas de dynamiques des communautés. En conclusion, ce travail ouvre la voie à une meilleure considération et une meilleure compréhension du rôle des variabilités intra-spécifiques dans les dynamiques des communautés végétales. / Mountain grasslands provide numerous ecosystem services that are likely to be impacted by global change. Plant functional traits hold great promise to succinctly characterise plant community response to changing environmental conditions and its effect on associated services; with growing evidence of the importance of intra-specific trait variability. I propose here a novel agent-based model, MountGrass, that combines the modelling of species rich grassland communities with phenotypic plasticity. These two key components are integrated via allocation trade-offs based on established empirical patterns of strategic differentiation in resource-use.With MountGrass, I explored the impact of phenotypic plasticity on individual plant growth and on main properties of grassland communities. At the individual level, the parametrised model revealed a strong impact of plasticity on growth and species’ fundamental niches, with potentially large impacts on community properties. These effects are explained by the convergence of species’ strategies and the reduction of the sensitivity to variable conditions. At the community level, simulations confirmed the strong effect of plastic allocation on community structure and species richness. These effects are driven by the cumulative effect of a reduction of both abiotic filtering and fitness differences between species. However, no clear effect on the dominant strategy or productivity could be detected.Going further, the robustness of these findings and other patterns of community dynamics should be analysed with alternative or extended implementations of MountGrass. In sum, this work opens a door towards a better integration and understanding of the role of the intra-specific variability in complex plant community dynamics.

La gouvernance pour le développement durable comporte de nombreux défis. L'un de ces défis consiste à mieux comprendre les systèmes socio-écologiques gouvernés. Dans de tels systèmes, l'apprentissage par essais et erreurs implique le risque de conséquences inattendues, irréversibles et néfastes. De plus, en raison de la complexité des systèmes socio-écologiques, les leçons tirées d'expériences à petite échelle ne peuvent pas toujours être applicables à des problèmes à grande échelle. Un autre aspect difficile des problèmes de développement durable est que ces problèmes sont souvent multidisciplinaires et composés de composants qui sont chacun étudiés individuellement dans une discipline différente, mais il existe peu d'informations sur leur comportement ensemble. Un troisième défi de la gouvernance pour le développement durable est qu'il est souvent nécessaire d'impliquer les parties prenantes dans des actions de gestion et des mesures d'intervention coûteuses pour les individus qui y participent. De plus, dans de nombreuses situations de ce type, les incitations financières et l'application des réglementations se soldent par un échec et ne constituent donc pas des options de gouvernance. Dans cette thèse, les défis ci-dessus sont abordés dans un exemple de contrôle des perturbations forestières avec une approche intégrée. Pour éviter le problème des effets indésirables irréversibles et pour permettre des expériences répétées, une approche de simulation est utilisée. Pour relever le défi de la multidisciplinarité des problèmes des systèmes socio-écologiques, deux modèles sont développés indépendamment - portant sur les aspects sociaux et écologiques du système de l'étude - et ils sont ensuite couplés de telle sorte que la sortie de chaque modèle est utilisée comme entrée pour l'autre modèle. Pour résoudre le problème de l'engagement des parties prenantes, un plan est proposé pour la promotion d'un comportement respectueux de l'environnement. Ce plan est basé sur l'offre de reconnaissance à ceux qui adoptent volontairement le comportement responsable. Le modèle écologique de cette étude, qui simule la propagation d'une perturbation forestière, est construit à l'aide de l’apprentissage automatique supervisé. Le modèle social de cette étude, qui simule l'émergence d'une nouvelle norme de comportement, est construit à l'aide de l'apprentissage par renforcement. Les deux modèles sont testés et validés avant couplage. Le modèle couplé est ensuite utilisé comme un laboratoire virtuel, où plusieurs expériences sont réalisées dans un cadre hypothétique et selon différents scénarios. Chacune de ces expériences est une simulation. A travers ces simulations, cette étude montre qu'avec un algorithme de prise de décision approprié et avec suffisamment de temps pour l'interaction entre une entité gouvernante et la société, il est possible de créer une motivation pour un comportement responsable dans la société. En d'autres termes, il est possible d'encourager la participation volontaire des acteurs à l'action pour le développement durable, sans que l'entité gouvernante ait besoin d'utiliser des incitations financières ou d'imposer son autorité. Ces résultats peuvent être applicables à d'autres contextes où un comportement responsable des individus ou des entreprises est recherché afin d'atténuer l'impact d'une perturbation, de protéger une ressource écologique, ou de faciliter une transition sectorielle vers la durabilité. / Governance for sustainable development involves many challenges. One of those challenges is to gain insight about the social-ecological systems being governned. In such systems, learning by trial and error involve the risk of unexpected, irreversible and adverse consequences. Moreover, due to complexity of social-ecological systems, lessons learned from small scale experiments may not be applicable in large-scale problems. Another challenging aspect of problems of sustainable development is that these problems are often multidisciplinary and comprised of components that are each studied individually in a different discipline, but little information exists about their behavior together as a whole. A third challenge in governance for sustainable development is that often it is necessary to involve stakeholders in management actions and intervention measures that are costly for individuals who participate in them. Moreover, in many of these situations financial incentives or enforcement of regulations result in failure, and are thus not options for governance. In this thesis, the above challenges are addressed in an example case of forest disturbance control with an integrated approach. To avoid the problem of irreversible adverse effects and to allow repeated experiments, a simulation approach is used. To tackle the challenge of multidisciplinarity of problems of social-ecological systems, two models are independently developed – pertaining to social and ecological aspects of the system of the study – and they are subsequently coupled in such a way that the output of each model served as an input for the other. To address the problem of engagement of stakeholders, a scheme is proposed for promotion of environmentally responsible behavior. This scheme is based on offering recognition to those who voluntarily perform the responsible behavior. The ecological model of this study, which simulates the spread of a forest disturbance, is built using Supervised Machine Learning. The social model of this study, which simulates the emergence of a new norm of behavior, is built using Reinforcement Learning. Both models are tested and validated before coupling. The coupled model is then used as a virtual laboratory, where several experiments are performed in a hypothetical setting and under various scenarios. Each such experiment is a simulation. Through these simulations, this study shows that with an appropriate decision-making algorithm and with sufficient time for interaction between a governing entity and the society, it is possible to create motivation for responsible behavior in the society. In other words, it is possible to encourage voluntary participation of stakeholders in action for sustainable development, without the need for the governing entity to use financial incentives or impose its authority. These results may be applicable to other contexts where responsible behavior by individuals or enterprises is sought in order to mitigate the impact of a disturbance, protect an ecological resource, or facilitate a sectoral transition towards sustainability.

Linked to climate change, drivers such as increased temperatures and decreased water availability affect forest health in complex ways by simultaneously weakening tree vitality and promoting insect pest activity. One major beneficiary of climate-induced changes is the European spruce bark beetle (Ips typographus). To improve the mechanistic understanding of climate change impacts on long-term beetle infestation risks, individual-based simulation models (IBM) such as the bark beetle dispersion model IPS-SPREADS have been proven as effective tools. However, the computational costs of IBMs limit their spatial scale of application. While these tools are best suitable to simulate bark beetle dynamics on the plot level, upscaling the process to larger areas is challenging. The larger spatial scale is, nevertheless, often required to support the selection of adequate management intervention. Here, we introduce a novel two-step approach to address this challenge: (1) we use the IPS-SPREADS model to simulate the bark beetle dispersal at a local scale by dividing the research area into 250 × 250 m grid cells; and (2) we then apply a metamodel framework to upscale the results to the landscape level. The metamodel is based on Markov chains derived from the infestation probabilities of IPS-SPREADS results and extended by considering neighbor interaction and spruce dieback of each focal cell. We validated the metamodel by comparing its predictions with infestations observed in 2017 and 2018 in the Saxon Switzerland national park, Germany, and tested sanitation felling as a measure to prevent potential further outbreaks in the region. Validation showed an improvement in predictions by introducing the model extension of beetle spreading from one cell to another. The metamodel forecasts indicated an increase in the risk of infestation for adjacent forest areas. In case of a beetle mass outbreak, sanitation felling intensities of 80 percent and above seem to mitigate further outbreak progression.

<p dir="ltr">Tuberculosis (TB), caused by <i>Mycobacterium tuberculosis</i> (<i>Mtb</i>), and human immunodeficiency virus-1 (HIV) are major public health concerns, individually and in combination. The status of the host immune system, previous <i>Mtb</i> infection and HIV-mediated T cell exhaustion, can have significant impacts on immune dynamics during reinfection. Individuals with asymptomatic latent TB infection (LTBI) may be protected against <i>Mtb </i>reinfection, as demonstrated by animal and <i>in vitro </i>studies. However, the underlying dynamics and protective mechanisms of LTBI are poorly understood. In HIV, long-term infection in children and associated T cell exhaustion leads to weakened immune responses to HIV reinfection. The complexity of these infections, particularly in the context of the heightened vulnerability of HIV+ individuals to TB, underscores the need for novel investigative approaches to study host-pathogen and pathogen-pathogen interactions. To this, we have developed an agent-based model (ABM) as a mechanistic computational tool to simulate the immune response to <i>Mtb </i>and HIV, separately and during coinfection. Our ABM integrates clinical and experimental data; simulates immune cell dynamics between macrophages, CD4+ and CD8+ T cells; and produces emergent granuloma-like structures – a critical response to <i>Mtb</i>. This <i>in silico</i> approach allows us to efficiently explore host-pathogen interactions and their clinical implications. By unraveling the complex interplay of immune cell activation, T cell exhaustion, and pathogen dynamics, our model offers insights that could guide the development of targeted therapies. By quantifying the multifaceted nature of these diseases and their interactions, we highlight the potential of computational approaches in understanding and treating complex diseases, individually and in combination.</p>

<p dir="ltr">Wound healing is a complex biological process orchestrated by intricate cellular and biochemical interactions. This study leverages a multiscale modeling approach, integrating agent-based and ordinary differential equation (ODE) methods within CompuCell3D, to investigate wound detection and calcium signaling in juvenile zebrafish. Calcium as a ubiquitous secondary messenger plays a crucial role in translating wound stimuli into cellular responses. We focus on the initial phase of wound detection, a multi-step process beginning at the subcellular level with the release of Damage-Associated Molecular Patterns (DAMPs) and subsequent calcium signaling. We hypothesize that an ATP diffusion wave acts as the primary trigger, initiating a downstream calcium signaling cascade mediated by inositol triphosphate (IP3). Calcium and IP3 production and movement from the injured cells to healthy ones would then coordinate a tightly regulated wound response. To investigate this hypothesis, we adapted existing equations from a Drosophila wing disc injury model. We carefully modified them to accurately represent the zebrafish system in our in-silico setup, specifically focusing on relevant agonists. Model predictions were rigorously compared to the zebrafish’s experimental data to validate the computational approach. Our findings provide preliminary evidence suggesting that ATP diffusion through the interstitial spaces of injured tissue may be a potent agonist, triggering localized calcium release closely resembling experimental observations. This multiscale modeling framework offers a promising avenue for significant advancements in wound healing research. It has the potential to facilitate the development of novel therapeutic strategies and discoveries by enabling the integration of cell signaling pathways and tissue engineering.</p>

Diese Dissertation umfasst drei Aufsätzen, die sich mit Erwartungen, Entscheidungen und deren Rückwirkung auf die Umgebung beschäftigen. Der erste Aufsatz untersucht die Binnenwanderung von Ost- nach Westdeutschland. Dabei wird der Zusammenhang von Variation in ökonomischen Disparitäten zwischen der Ursprungs- und der Zielregion und Bildungsniveau, Alter und Arbeitsmarktstatus der wandernden Bevölkerung untersucht. Mit Hilfe der SOEP Daten von 1993 bis 2011 gelangt die Untersuchung zu dem Ergebnis, dass regionale Disparitäten in Verbindung mit der Selbstselektion der Wandernden stehen. Während die Wandernden im Durchschnitt jünger und besser ausgebildet als die Bleibenden sind, verringert sich dieser Unterschied, wenn die Differentiale in den Arbeitslosenquoten zwischen den Regionen steigen. Im zweiten Aufsatz entwickle ich ein Modell zur Untersuchung von prosozialem Verhalten in Begegnungen mit Fremden. Durch das Abstrahieren von Möglichkeiten der Reputationsbildung oder des Bestraftwerdens, entfallen die wesentlichen strategischen Motive für prosoziales Verhalten. Die Entscheidung prosozial zu Handeln ist dann nicht mehr strategisch vorteilhaft sondern intrinsisch motiviert durch Altruismus und einer Neigung sich an das Verhalten anderer anzupassen. In einem zweiten Schritt untersuche ich, ob die Erkenntnisse des Modells mit dem empirisch beobachteten Verhalten übereinstimmen. Der dritte Aufsatz skizziert eine (mögliche) Verhaltensstruktur und notwendige Bedingungen auf Mikroebene, die zu den beobachteten Verhaltensunterschieden in prosozialem Verhalten zwischen dem ländlichen und städtischen Raum führen. Den Rahmen des hier entwickelten Modells bildet das bekannte Gefangenen Dilemma, das wiederholt mit zufällig zugeordneten Partnern einer großen Gesellschaft gespielt wird. Das Modell bezieht Merkmale ein, die sich häufig in realen Begegnungen wiederfinden: imperfekte Information, freiwillige Teilnahme und eine Neigung sich dem Verhalten anderer anzupassen. / This thesis consists of three essays that analyze choices and beliefs to explore how both lead to adaptive behavior. The first essay examines the positive net migration flow from the eastern to western parts of Germany. The migration decision is substantially based on expectations about future developments. With economic conditions changing substantially over the past 20 years in the eastern part of Germany, the incentives to migrate have also altered, so changing the composition of the east-to-west migrant body. This essay explores variations in economic disparities between the region of origin and region of destination, relating them to changes in the skill level, age and labor force status of the migrant population. Analyzing SOEP data from 1993-2011, the findings suggest that, with falling wage differentials, older migrants are less frequent job-to-job movers and are more likely to be non-working prior to migration. Furthermore, while migrants tend to be younger and better educated than stayers, the group of movers becomes partly less distinct from the group of stayers with respect to the skill and age composition when regional disparities in employment opportunities increase. The second and the third essay of this thesis model the decision making process in social interactions between strangers. In these situations, choices are often affected by beliefs about others behavior. In the second essay of this work, I develop a simple model of prosocial behavior for encounters between strangers. By abstracting from the possibility of reputation building and punishment between anonymous partners, I remove the main strategic motives for prosocial behavior so reducing it to a simple non-strategic decision. The principal motivation to behave prosocially is then intrinsic, based on altruism, with a taste for conforming to the behavior of others. In this way, individual decisions are conditional on the behavior of others. Emerging equilibria will then explain the occurrence of prosocial or cooperative behavior within a given society. In a second step, I analyze whether the model’s predictions are consistent with the empirical evidence on the link between beliefs and prosocial behavior using data on blood donations. The third essay outline a (possible) micro-structure and conditions which lead to the observed urban-rural differences in cooperative behavior using agent-based modeling. The model presented here adapts the familiar framework of a prisoners dilemma which is played repeatedly with randomly matched members of a large population. I introduce features that are often found in real world interactions: imperfect information, voluntary participation and a taste for conforming to majority behavior. In this analysis, peoples beliefs about the level of cooperation in the population and their resulting behavior are determined endogenously. Both are governed principally by the experience that they derive from interactions. I present results of an agentbased simulation in order to study the emerging dynamic relationships, to examine how cooperative behavior evolves over time under different circumstances, and to determine how urban-rural differences in behavior emerge. The factors that give rise to rural-urban differences are heterogeneity in individual loss aversion or risk taking, and limited migration possibilities between rural and urban areas.

Ansätze der mathematischen Modellierung ermöglichen die Analyse der dynamischen Eigenschaften biologischer Systeme und den Einfluß spezifischer Funktionen. Das Ziel dieser Arbeit ist es verschiedene Aspekte der Interaktionen zwischen Wirt und Krankheitserregern zu analysieren. In Kapitel 3 diskutiere ich ein Modell der zellulären Antwort auf Hitzeschockstress im Pilz Candida albicans. Das Modell in Form von gewöhnlichen Differentialgleichungen erörtert mehrere Aspekte des Systems, wie z.B. die erworbene Thermotoleranz und eine perfekte Anpassung an die Beanspruchung durch die Temperaturwechsel. Im Rahmen der Interaktionen zwischen Wirt und Krankheitserreger ist die Studie relevant, da die Entwicklung von Fieber eine primäre Antwort des Organismus auf eine Pilzinvasion ist. Die Dynamik von C. albicans Virulenzfaktoren, wie z.B. der Übergang vom Hefe- zum Hyphenstadium, und die Abwehrmechanismen des Wirts bestimmen den Zustand des Pilzes, d.h. ob er als Kommensale oder Krankheitserreger vorkommt. Mit Hilfe einer agenten-basierten Modellierungstechnik, in Kapitel 4, untersuche ich die Auswirkungen potenzieller medikamentöser Behandlungen von Pilzpopulationen und ihre Effektivität. In Kapitel 5 analysiere ich die Dynamik der C. albicans Hefe- und Hyphenpopulationen unter der Annahme, das zwischen den Individuen beider Populationen paarweise Wechselwirkungen bestehen, die zusätzlich von Fresszellen und Ernährungsbedingungen beeinflusst werden. Das erste Modell basiert auf den Prinzipien der Spieltheorie. Aus dieser Studie lässt sich die Hypothese aufstellen, dass sich im Verlauf der Infektion die evolutionäre Spieldynamik von der Snowdrift Spieldynamik in Richtung Gefangendilemma verschiebt. Im zweiten Modell untersuche ich die Umschaltraten zwischen Hefen und Hyphen. Das Modell zeigt, dass in Pilzpopulationen die Ausprägung verschiedener Phänotypen der Grund für die erhöhte Überlebensfähigkeit der Population sein könnte. / Mathematical modeling approaches facilitate the analysis of dynamic properties of mechanisms triggering specific functions of biological systems. Through this work I aim to shed light on various aspects of host-pathogen interactions. In Chapter 3, I discuss a model of heat shock stress response activated in the fungus Candida albicans. The model in form of ordinary differential equations reveals several features of the system, such as acquired thermotolerance and a perfect molecular adaptation to the thermal insult. The study is relevant in the context of host-pathogen interactions since development of fever is a primary host response to fungal invasion. The dynamics of C. albicans virulence factors, e.g., yeast to hypha transition, and defense mechanisms of the host determine the state of the fungi, i.e. whether to act as a commensal or as a foe. Through application of an agent-based modeling technique, in Chapter 4, I investigate effects of potential drug treatments on fungal populations and their effectivity in the fungal clearance. In Chapter 5, I analyze the dynamics of candida yeast and hyphal populations assuming pairwise interactions influenced by phagocytic cells and nutritional conditions. The first model is based on game theory principles. From the study it can be hypothesized that during the course of infection the evolutionary game dynamics shift from Snowdrift game dynamics toward Prisoners’ dilemma. In the second model, I examine switching rates between yeast and hypha. The model reveals that phenotypic variations may occur in order to increase the fitness of the population.