Policy Diffusion: An Agent-Based Approach

Methods like Event History Analysis can show the existence of diffusion and part of its nature, but do not study the process itself. Nowadays, thanks to the increasing performance of computers, processes can be studied using computational modeling. This thesis presents an agent-based model of policy diffusion mainly inspired from the model developed by Braun and Gilardi (2006). I first start by developing a theoretical framework of policy diffusion that presents the main internal drivers of policy diffusion - such as the preference for the policy, the effectiveness of the policy, the institutional constraints, and the ideology - and its main mechanisms, namely learning, competition, emulation, and coercion. Therefore diffusion, expressed by these interdependencies, is a complex process that needs to be studied with computational agent-based modeling. In a second step, computational agent-based modeling is defined along with its most significant concepts: complexity and emergence. Using computational agent-based modeling implies the development of an algorithm and its programming. When this latter has been developed, we let the different agents interact. Consequently, a phenomenon of diffusion, derived from learning, emerges, meaning that the choice made by an agent is conditional to that made by its neighbors. As a result, learning follows an inverted S-curve, which leads to partial convergence - global divergence and local convergence - that triggers the emergence of political clusters; i.e. the creation of regions with the same policy. Furthermore, the average effectiveness in this computational world tends to follow a J-shaped curve, meaning that not only time is needed for a policy to deploy its effects, but that it also takes time for a country to find the best-suited policy. To conclude, diffusion is an emergent phenomenon from complex interactions and its outcomes as ensued from my model are in line with the theoretical expectations and the empirical evidence.Les méthodes d'analyse de biographie (event history analysis) permettent de mettre en évidence l'existence de phénomènes de diffusion et de les décrire, mais ne permettent pas d'en étudier le processus. Les simulations informatiques, grâce aux performances croissantes des ordinateurs, rendent possible l'étude des processus en tant que tels. Cette thèse, basée sur le modèle théorique développé par Braun et Gilardi (2006), présente une simulation centrée sur les agents des phénomènes de diffusion des politiques. Le point de départ de ce travail met en lumière, au niveau théorique, les principaux facteurs de changement internes à un pays : la préférence pour une politique donnée, l'efficacité de cette dernière, les contraintes institutionnelles, l'idéologie, et les principaux mécanismes de diffusion que sont l'apprentissage, la compétition, l'émulation et la coercition. La diffusion, définie par l'interdépendance des différents acteurs, est un système complexe dont l'étude est rendue possible par les simulations centrées sur les agents. Au niveau méthodologique, nous présenterons également les principaux concepts sous-jacents aux simulations, notamment la complexité et l'émergence. De plus, l'utilisation de simulations informatiques implique le développement d'un algorithme et sa programmation. Cette dernière réalisée, les agents peuvent interagir, avec comme résultat l'émergence d'un phénomène de diffusion, dérivé de l'apprentissage, où le choix d'un agent dépend en grande partie de ceux faits par ses voisins. De plus, ce phénomène suit une courbe en S caractéristique, poussant à la création de régions politiquement identiques, mais divergentes au niveau globale. Enfin, l'efficacité moyenne, dans ce monde simulé, suit une courbe en J, ce qui signifie qu'il faut du temps, non seulement pour que la politique montre ses effets, mais également pour qu'un pays introduise la politique la plus efficace. En conclusion, la diffusion est un phénomène émergent résultant d'interactions complexes dont les résultats du processus tel que développé dans ce modèle correspondent tant aux attentes théoriques qu'aux résultats pratiques.

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

A bio-inspired agent-based programming environment for pervasive platforms

Abstract in English : Ubiquitous Computing is the emerging trend in computing systems. Based on this observation this thesis proposes an analysis of the hardware and environmental constraints that rule pervasive platforms. These constraints have a strong impact on the programming of such platforms. Therefore solutions are proposed to facilitate this programming both at the platform and node levels. The first contribution presented in this document proposes a combination of agentoriented programming with the principles of bio-inspiration (Phylogenesys, Ontogenesys and Epigenesys) to program pervasive platforms such as the PERvasive computing framework for modeling comPLEX virtually Unbounded Systems platform. The second contribution proposes a method to program efficiently parallelizable applications on each computing node of this platform. Résumé en Français : Basée sur le constat que les calculs ubiquitaires vont devenir le paradigme de programmation dans les années à venir, cette thèse propose une analyse des contraintes matérielles et environnementale auxquelles sont soumises les plateformes pervasives. Ces contraintes ayant un impact fort sur la programmation des plateformes. Des solutions sont donc proposées pour faciliter cette programmation tant au niveau de l'ensemble des noeuds qu'au niveau de chacun des noeuds de la plateforme. La première contribution présentée dans ce document propose d'utiliser une alliance de programmation orientée agent avec les grands principes de la bio-inspiration (Phylogénèse, Ontogénèse et Épigénèse). Ceci pour répondres aux contraintes de programmation de plateformes pervasives comme la plateforme PERvasive computing framework for modeling comPLEX virtually Unbounded Systems . La seconde contribution propose quant à elle une méthode permettant de programmer efficacement des applications parallélisable sur chaque noeud de calcul de la plateforme

Role of genetic and social factors in modulating the efficiency of division of labour in social insects

Summary : Division of labour is one of the most fascinating aspects of social insects. The efficient allocation of individuals to a multitude of different tasks requires a dynamic adjustment in response to the demands of a changing environment. A considerable number of theoretical models have focussed on identifying the mechanisms allowing colonies to perform efficient task allocation. The large majority of these models are built on the observation that individuals in a colony vary in their propensity (response threshold) to perform different tasks. Since individuals with a low threshold for a given task stimulus are more likely to perform that task than individuals with a high threshold, infra-colony variation in individual thresholds results in colony division of labour. These theoretical models suggest that variation in individual thresholds is affected by the within-colony genetic diversity. However, the models have not considered the genetic architecture underlying the individual response thresholds. This is important because a better understanding of division of labour requires determining how genotypic variation relates to differences in infra-colony response threshold distributions. In this thesis, we investigated the combined influence on task allocation efficiency of both, the within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes underlying the response thresholds. We used an agent-based simulator to model a situation where workers in a colony had to perform either a regulatory task (where the amount of a given food item in the colony had to be maintained within predefined bounds) or a foraging task (where the quantity of a second type of food item collected had to be the highest possible). The performance of colonies was a function of workers being able to perform both tasks efficiently. To study the effect of within-colony genetic diversity, we compared the performance of colonies with queens mated with varying number of males. On the other hand, the influence of genetic architecture was investigated by varying the number of loci underlying the response threshold of the foraging and regulatory tasks. Artificial evolution was used to evolve the allelic values underlying the tasks thresholds. The results revealed that multiple matings always translated into higher colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or few genes for the foraging task's threshold. By contrast, higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes determining the threshold for the regulatory task only had a minor but incremental effect on colony performance. Overall, our numerical experiments indicate the importance of considering the effects of queen mating frequency, genetic architecture underlying task thresholds and the type of task performed when investigating the factors regulating the efficiency of division of labour in social insects. In this thesis we also investigate the task allocation efficiency of response threshold models and compare them with neural networks. While response threshold models are widely used amongst theoretical biologists interested in division of labour in social insects, our simulation reveals that they perform poorly compared to a neural network model. A major shortcoming of response thresholds is that they fail at one of the most crucial requirement of division of labour, the ability of individuals in a colony to efficiently switch between tasks under varying environmental conditions. Moreover, the intrinsic properties of the threshold models are that they lead to a large proportion of idle workers. Our results highlight these limitations of the response threshold models and provide an adequate substitute. Altogether, the experiments presented in this thesis provide novel contributions to the understanding of how division of labour in social insects is influenced by queen mating frequency and genetic architecture underlying worker task thresholds. Moreover, the thesis also provides a novel model of the mechanisms underlying worker task allocation that maybe more generally applicable than the widely used response threshold models. Resumé : La répartition du travail est l'un des aspects les plus fascinants des insectes vivant en société. Une allocation efficace de la multitude de différentes tâches entre individus demande un ajustement dynamique afin de répondre aux exigences d'un environnement en constant changement. Un nombre considérable de modèles théoriques se sont attachés à identifier les mécanismes permettant aux colonies d'effectuer une allocation efficace des tâches. La grande majorité des ces modèles sont basés sur le constat que les individus d'une même colonie diffèrent dans leur propension (inclination à répondre) à effectuer différentes tâches. Etant donné que les individus possédant un faible seuil de réponse à un stimulus associé à une tâche donnée sont plus disposés à effectuer cette dernière que les individus possédant un seuil élevé, les différences de seuils parmi les individus vivant au sein d'une même colonie mènent à une certaine répartition du travail. Ces modèles théoriques suggèrent que la variation des seuils des individus est affectée par la diversité génétique propre à la colonie. Cependant, ces modèles ne considèrent pas la structure génétique qui est à la base des seuils de réponse individuels. Ceci est très important car une meilleure compréhension de la répartition du travail requière de déterminer de quelle manière les variations génotypiques sont associées aux différentes distributions de seuils de réponse à l'intérieur d'une même colonie. Dans le cadre de cette thèse, nous étudions l'influence combinée de la variabilité génétique d'une colonie (qui prend son origine dans la variation du nombre d'accouplements des reines) avec le nombre de gènes supportant les seuils de réponse, vis-à-vis de la performance de l'allocation des tâches. Nous avons utilisé un simulateur basé sur des agents pour modéliser une situation où les travailleurs d'une colonie devaient accomplir une tâche de régulation (1a quantité d'une nourriture donnée doit être maintenue à l'intérieur d'un certain intervalle) ou une tâche de recherche de nourriture (la quantité d'une certaine nourriture doit être accumulée autant que possible). Dans ce contexte, 'efficacité des colonies tient en partie des travailleurs qui sont capable d'effectuer les deux tâches de manière efficace. Pour étudier l'effet de la diversité génétique d'une colonie, nous comparons l'efficacité des colonies possédant des reines qui s'accouplent avec un nombre variant de mâles. D'autre part, l'influence de la structure génétique a été étudiée en variant le nombre de loci à la base du seuil de réponse des deux tâches de régulation et de recherche de nourriture. Une évolution artificielle a été réalisée pour évoluer les valeurs alléliques qui sont à l'origine de ces seuils de réponse. Les résultats ont révélé que de nombreux accouplements se traduisaient toujours en une plus grande performance de la colonie, quelque soit le nombre de loci encodant les seuils des tâches de régulation et de recherche de nourriture. Cependant, les effets bénéfiques d'accouplements additionnels ont été particulièrement important lorsque la structure génétique des reines comprenait un ou quelques gènes pour le seuil de réponse pour la tâche de recherche de nourriture. D'autre part, un nombre plus élevé de gènes encodant la tâche de recherche de nourriture a diminué la performance de la colonie avec un effet nuisible d'autant plus fort lorsque les reines s'accouplent avec plusieurs mâles. Finalement, le nombre de gènes déterminant le seuil pour la tâche de régulation eu seulement un effet mineur mais incrémental sur la performance de la colonie. Pour conclure, nos expériences numériques révèlent l'importance de considérer les effets associés à la fréquence d'accouplement des reines, à la structure génétique qui est à l'origine des seuils de réponse pour les tâches ainsi qu'au type de tâche effectué au moment d'étudier les facteurs qui régulent l'efficacité de la répartition du travail chez les insectes vivant en communauté. Dans cette thèse, nous étudions l'efficacité de l'allocation des tâches des modèles prenant en compte des seuils de réponses, et les comparons à des réseaux de neurones. Alors que les modèles basés sur des seuils de réponse sont couramment utilisés parmi les biologistes intéressés par la répartition des tâches chez les insectes vivant en société, notre simulation montre qu'ils se révèlent peu efficace comparé à un modèle faisant usage de réseaux de neurones. Un point faible majeur des seuils de réponse est qu'ils échouent sur un point crucial nécessaire à la répartition des tâches, la capacité des individus d'une colonie à commuter efficacement entre des tâches soumises à des conditions environnementales changeantes. De plus, les propriétés intrinsèques des modèles basés sur l'utilisation de seuils conduisent à de larges populations de travailleurs inactifs. Nos résultats mettent en évidence les limites de ces modèles basés sur l'utilisation de seuils et fournissent un substitut adéquat. Ensemble, les expériences présentées dans cette thèse fournissent de nouvelles contributions pour comprendre comment la répartition du travail chez les insectes vivant en société est influencée par la fréquence d'accouplements des reines ainsi que par la structure génétique qui est à l'origine, pour un travailleur, du seuil de réponse pour une tâche. De plus, cette thèse fournit également un nouveau modèle décrivant les mécanismes qui sont à l'origine de l'allocation des tâches entre travailleurs, mécanismes qui peuvent être appliqué de manière plus générale que ceux couramment utilisés et basés sur des seuils de réponse.

Task-dependent influence of genetic architecture and mating frequency on division of labour in social insect societies.

Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task's threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.

What makes articles highly cited?

We examined drivers of article citations using 776 articles that were published from 1990-2012 in a broad-based and high-impact social sciences journal, The Leadership Quarterly. These articles had 1,191 unique authors having published and received in total (at the time of their most recent article published in our dataset) 16,817 articles and 284,777 citations, respectively. Our models explained 66.6% of the variance in citations and showed that quantitative, review, method, and theory articles were significantly more cited than were qualitative articles or agent-based simulations. As concerns quantitative articles, which constituted the majority of the sample, our model explained 80.3% of the variance in citations; some methods (e.g., use of SEM) and designs (e.g., meta-analysis), as well as theoretical approaches (e.g., use of transformational, charismatic, or visionary type-leadership theories) predicted higher article citations. Regarding the statistical conclusion validity of quantitative articles, articles having endogeneity threats received significantly fewer citations than did those using a more robust design or an estimation procedure that ensured correct causal estimation. We make several general recommendations on how to improve research practice and article citations.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Merkel cells and the individuality of friction ridge skin

There is no definite theory yet for the mechanism by which the pattern of epidermal ridges on fingers, palms and soles forming friction ridge skin (FRS) patterns is created. For a long time growth forces in the embryonal epidermis have been believed to be involved in FRS formation. More recent evidence suggests that Merkel cells play an important part in this process as well. Here we suggest a model for the formation of FRS patterns that links Merkel cells to the epidermal stress distribution. The Merkel cells are modeled as agents in an agent based model that move anisotropically where the anisotropy is created by the epidermal stress tensor. As a result ridge patterns are created with pattern defects as they occur in real FRS patterns. As a consequence we suggest why the topology of FRS patterns is indeed unique as the arrangement of pattern defects is sensitive to the initial configuration of Merkel cells.

On learning dynamics underlying the evolution of learning rules.

In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

What matters for predicting spatial distributions of trees: techniques, data, or species' characteristics?

Data characteristics and species traits are expected to influence the accuracy with which species' distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive power and sensitivity to location error, change in map resolution, and sample size, and assess whether some species traits can explain variation in model performance. We focused on 30 native tree species in Switzerland and used presence-only data to model current distribution, which we evaluated against independent presence-absence data. While there are important differences between the predictive performance of modeling methods, the variance in model performance is greater among species than among techniques. Within the range of data perturbations in this study, some extrinsic parameters of data affect model performance more than others: location error and sample size reduced performance of many techniques, whereas grain had little effect on most techniques. No technique can rescue species that are difficult to predict. The predictive power of species-distribution models can partly be predicted from a series of species characteristics and traits based on growth rate, elevational distribution range, and maximum elevation. Slow-growing species or species with narrow and specialized niches tend to be better modeled. The Swiss presence-only tree data produce models that are reliable enough to be useful in planning and management applications.

Deposits of the sandy braided South Saskatchewan River: Implications for the use of modern analogs in reconstructing channel dimensions in reservoir characterization

Estimation of the dimensions of fluvial geobodies from core data is a notoriously difficult problem in reservoir modeling. To try and improve such estimates and, hence, reduce uncertainty in geomodels, data on dunes, unit bars, cross-bar channels, and compound bars and their associated deposits are presented herein from the sand-bed braided South Saskatchewan River, Canada. These data are used to test models that relate the scale of the formative bed forms to the dimensions of the preserved deposits and, therefore, provide an insight as to how such deposits may be preserved over geologic time. The preservation of bed-form geometry is quantified by comparing the Alluvial architecture above and below the maximum erosion depth of the modem channel deposits. This comparison shows that there is no significant difference in the mean set thickness of dune cross-strata above and below the basal erosion surface of the contemporary channel, thus suggesting that dimensional relationships between dune deposits and the formative bed-form dimensions are likely to be valid from both recent and older deposits. The data show that estimates of mean bankfull flow depth derived from dune, unit bar, and cross-bar channel deposits are all very similar. Thus, the use of all these metrics together can provide a useful check that all components and scales of the alluvial architecture have been identified correctly when building reservoir models. The data also highlight several practical issues with identifying and applying data relating to cross-strata. For example, the deposits of unit bars were found to be severely truncated in length and width, with only approximately 10% of the mean bar-form length remaining, and thus making identification in section difficult. For similar reasons, the deposits of compound bars were found to be especially difficult to recognize, and hence, estimates of channel depth based on this method may be problematic. Where only core data are available (i.e., no outcrop data exist), formative flow depths are suggested to be best reconstructed using cross-strata formed by dunes. However, theoretical relationships between the distribution of set thicknesses and formative dune height are found to result in slight overestimates of the latter and, hence, mean bankfull flow depths derived from these measurements. This article illustrates that the preservation of fluvial cross-strata and, thus, the paleohydraulic inferences that can be drawn from them, are a function of the ratio of the size and migration rate of bed forms and the time scale of aggradation and channel migration. These factors must thus be considered when deciding on appropriate length:thickness ratios for the purposes of object-based modeling in reservoir characterization.

Preliminary regional rockfall hazard mapping using LIDAR-based slope frequency distribution and CONEFALL modeling

A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.