Knowledge diffusion networks consist of individuals who exchange knowledge and knowledge flows connecting the individuals. By studying knowledge diffusion in a network perspective, it helps us understand how the connections between individuals affect the knowledge diffusion processes. Existing research on knowledge diffusion networks mostly adopts a uni-dimensional perspective, where all the individuals in the networks are assumed to be of the same type. It also assumes that there is only one type of knowledge flow in the network. This dissertation proposes a multi-dimensional perspective of knowledge diffusion networks and examines the patterns of knowledge diffusion with Exponential Random Graph Model (ERGM) based approaches. The objective of this dissertation is to propose a framework that effectively addresses the multi-dimensionality of knowledge diffusion networks, to enable researchers and practitioners to conceptualize the multi-dimensional knowledge diffusion networks in various domains, and to provide implications on how to stimulate and control the knowledge diffusion process. The dissertation consists of three essays, all of which examine the multi-dimensional knowledge diffusion networks in a specific context, but each focuses on a different aspect of knowledge diffusion. Chapter 2 focuses on how structural properties of networks affect various types of knowledge diffusion processes in the domain of commercial technology. The study uses ERGM to simultaneously model multiple types of knowledge flows and examine their interactions. The objective is to understand the impacts of network structures on knowledge diffusion processes. Chapter 3 focuses on examining the impact of individual attributes and the attributes of knowledge on knowledge diffusion in the context of scientific innovation. Based on social capital theory, the study also utilizes ERGM to examine how knowledge transfer and knowledge co-creation can be affected by the attributes of individual researchers and the attributes of scientific knowledge. Chapter 4 considers the dynamic aspect of knowledge diffusion and proposes a novel network model extending ERGM to identify dynamic patterns of knowledge diffusion in social media. In the proposed model, dynamic patterns in social media networks are modeled based on the nodal attributes of individuals and the temporal information of network ties.

Appréhender l’organisation spatiale d’un territoire urbain ou périurbain génère un vaste champ de questionnements concernant la distribution et les propriétés du bâti, du parcellaire et des voies de circulation, et les interrelations de cet ensemble d’objets géographiques avec les usages de la cité. Cette thèse a pour objectif de proposer un modèle de représentation et de quantifier la structuration d’un tel espace afin de mieux en appréhender les usages. Cette démarche de modélisation repose sur la caractérisation des relations spatiales existantes entre les éléments remarquables identifiés. Afin de prendre en compte les entités d’un tel territoire et les relations spatiales qui les caractérisent, nous caractérisons un modèle de graphe où les noeuds représentent respectivement les bâtiments, les parcelles, et les routes, et les arcs correspondent aux relations topologiques de connexion, adjacence ou intersection, de ces éléments. Afin de quantifier les propriétés d’un territoire, une mesure de centralité du bâti, une mesure de connectivité locale du bâti, une mesure de densité du bâti et une mesure de la compacité du réseau de circulation sont proposées et formalisées. Ces mesures sont adaptables aux contextes ruraux, périurbains et urbains grâce aux paramètres permettant d’ajuster l’échelle d’observation et d’analyse. Le modèle et les mesures proposés sont implémentés dans le Système de Gestion de Bases de Données relationnel PostgreSQL avec prise en compte de l’extension spatiale PostGIS pour des applications grand public. L’application sur un cas d’étude, la commune de Guissény, tend à rendre opérationnel le modèle de graphe proposé et permet d’examiner les capacités d’analyse de la structuration spatiale de chaque mesure identifiée. / Understanding the spatial organization of a given territory generates a wide range of urban planning and research issues such as the distribution and properties of buildings, parcels and roads, and the relevance of it in terms of uses. The research developed by this thesis model the structuring of space, this being one of the first steps towards a better characterization, study, interpretation and simulation of the evolution of such objects.The structuring of space relies on the characterization of the spatial relationships between remarkable elements: buildings, parcels and road networks. Since existing models do not combine these elements, this thesis proposes a graph model that integrates all of them. The nodes represent buildings, parcels, and roads respectively, and the arcs correspond to the topological connection relationships, adjacency or intersection, of these elements.In order to quantify the properties that emerges from a given territory, a building centrality measure, a building local connectivity measure, a building density measure and a road network compactness measure have been proposed and formalized. These measures adapt to the rural, peri-urban and urban contexts thanks to the parameters that allow to adjust, scale of observation, and analysis. The model and measures proposed are implemented in the relational database management system PostgreSQL with PostGIS extension. The application on a case study, the village of Guisseny, makes the proposed graph model operational and allows to examine the spatial structuring analytical capacities of each measure.

[ES] La visión artificial es uno de los campos en mayor crecimiento en la actualidad que, junto con otras tecnologías como la Biometría o el Big Data, se ha convertido en el foco de interés de numerosas investigaciones y es considerada como una de las tecnologías del futuro. Este amplio campo abarca diversos métodos entre los que se encuentra el procesamiento y análisis de imágenes digitales. El éxito del análisis de imágenes y otras tareas de procesamiento de alto nivel, como pueden ser el reconocimiento de patrones o la visión 3D, dependerá en gran medida de la buena calidad de las imágenes de partida. Hoy en día existen multitud de factores que dañan las imágenes dificultando la obtención de imágenes de calidad óptima, esto ha convertido el (pre-) procesamiento digital de imágenes en un paso fundamental previo a la aplicación de cualquier otra tarea de procesado. Los factores más comunes son el ruido y las malas condiciones de adquisición: los artefactos provocados por el ruido dificultan la interpretación adecuada de la imagen y la adquisición en condiciones de iluminación o exposición deficientes, como escenas dinámicas, causan pérdida de información de la imagen que puede ser clave para ciertas tareas de procesamiento. Los pasos de (pre-)procesamiento de imágenes conocidos como suavizado y realce se aplican comúnmente para solventar estos problemas: El suavizado tiene por objeto reducir el ruido mientras que el realce se centra en mejorar o recuperar la información imprecisa o dañada. Con estos métodos conseguimos reparar información de los detalles y bordes de la imagen con una nitidez insuficiente o un contenido borroso que impide el (post-)procesamiento óptimo de la imagen. Existen numerosos métodos que suavizan el ruido de una imagen, sin embargo, en muchos casos el proceso de filtrado provoca emborronamiento en los bordes y detalles de la imagen. De igual manera podemos encontrar una enorme cantidad de técnicas de realce que intentan combatir las pérdidas de información, sin embargo, estas técnicas no contemplan la existencia de ruido en la imagen que procesan: ante una imagen ruidosa, cualquier técnica de realce provocará también un aumento del ruido. Aunque la idea intuitiva para solucionar este último caso será el previo filtrado y posterior realce, este enfoque ha demostrado no ser óptimo: el filtrado podrá eliminar información que, a su vez, podría no ser recuperable en el siguiente paso de realce. En la presente tesis doctoral se propone un modelo basado en teoría de grafos para el procesamiento de imágenes en color. En este modelo, se construye un grafo para cada píxel de tal manera que sus propiedades permiten caracterizar y clasificar dicho pixel. Como veremos, el modelo propuesto es robusto y capaz de adaptarse a una gran variedad de aplicaciones. En particular, aplicamos el modelo para crear nuevas soluciones a los dos problemas fundamentales del procesamiento de imágenes: suavizado y realce. Se ha estudiado el modelo en profundidad en función del umbral, parámetro clave que asegura la correcta clasificación de los píxeles de la imagen. Además, también se han estudiado las posibles características y posibilidades del modelo que nos han permitido sacarle el máximo partido en cada una de las posibles aplicaciones. Basado en este modelo se ha diseñado un filtro adaptativo capaz de eliminar ruido gaussiano de una imagen sin difuminar los bordes ni perder información de los detalles. Además, también ha permitido desarrollar un método capaz de realzar los bordes y detalles de una imagen al mismo tiempo que se suaviza el ruido presente en la misma. Esta aplicación simultánea consigue combinar dos operaciones opuestas por definición y superar así los inconvenientes presentados por el enfoque en dos etapas. / [CAT] La visió artificial és un dels camps en major creixement en l'actualitat que, junt amb altres tecnlogies com la Biometria o el Big Data, s'ha convertit en el focus d'interés de nombroses investigacions i és considerada com una de les tecnologies del futur. Aquest ampli camp comprén diversos m`etodes entre els quals es troba el processament digital d'imatges i anàlisis d'imatges digitals. L'èxit de l'anàlisis d'imatges i altres tasques de processament d'alt nivell, com poden ser el reconeixement de patrons o la visió 3D, dependrà en gran manera de la bona qualitat de les imatges de partida. Avui dia existeixen multitud de factors que danyen les imatges dificultant l'obtenció d'imatges de qualitat òptima, açò ha convertit el (pre-) processament digital d'imatges en un pas fonamental previa la l'aplicació de qualsevol altra tasca de processament. Els factors més comuns són el soroll i les males condicions d'adquisició: els artefactes provocats pel soroll dificulten la inter- pretació adequada de la imatge i l'adquisició en condicions d'il·luminació o exposició deficients, com a escenes dinàmiques, causen pèrdua d'informació de la imatge que pot ser clau per a certes tasques de processament. Els passos de (pre-) processament d'imatges coneguts com suavitzat i realç s'apliquen comunament per a resoldre aquests problemes: El suavitzat té com a objecte reduir el soroll mentres que el real se centra a millorar o recuperar la informació imprecisa o danyada. Amb aquests mètodes aconseguim reparar informació dels detalls i bords de la imatge amb una nitidesa insuficient o un contingut borrós que impedeix el (post-)processament òptim de la imatge. Existeixen nombrosos mètodes que suavitzen el soroll d'una imatge, no obstant això, en molts casos el procés de filtrat provoca emborronamiento en els bords i detalls de la imatge. De la mateixa manera podem trobar una enorme quantitat de tècniques de realç que intenten combatre les pèrdues d'informació, no obstant això, aquestes tècniques no contemplen l'existència de soroll en la imatge que processen: davant d'una image sorollosa, qualsevol tècnica de realç provocarà també un augment del soroll. Encara que la idea intuïtiva per a solucionar aquest últim cas seria el previ filtrat i posterior realç, aquest enfocament ha demostrat no ser òptim: el filtrat podria eliminar informació que, al seu torn, podria no ser recuperable en el seguënt pas de realç. En la present Tesi doctoral es proposa un model basat en teoria de grafs per al processament d'imatges en color. En aquest model, es construïx un graf per a cada píxel de tal manera que les seues propietats permeten caracteritzar i classificar el píxel en quëstió. Com veurem, el model proposat és robust i capaç d'adaptar-se a una gran varietat d'aplicacions. En particular, apliquem el model per a crear noves solucions als dos problemes fonamentals del processament d'imatges: suavitzat i realç. S'ha estudiat el model en profunditat en funció del llindar, paràmetre clau que assegura la correcta classificació dels píxels de la imatge. A més, també s'han estudiat les possibles característiques i possibilitats del model que ens han permés traure-li el màxim partit en cadascuna de les possibles aplicacions. Basat en aquest model s'ha dissenyat un filtre adaptatiu capaç d'eliminar soroll gaussià d'una imatge sense difuminar els bords ni perdre informació dels detalls. A més, també ha permés desenvolupar un mètode capaç de realçar els bords i detalls d'una imatge al mateix temps que se suavitza el soroll present en la mateixa. Aquesta aplicació simultània aconseguix combinar dues operacions oposades per definició i superar així els inconvenients presentats per l'enfocament en dues etapes. / [EN] Computer vision is one of the fastest growing fields at present which, along with other technologies such as Biometrics or Big Data, has become the focus of interest of many research projects and it is considered one of the technologies of the future. This broad field includes a plethora of digital image processing and analysis tasks. To guarantee the success of image analysis and other high-level processing tasks as 3D imaging or pattern recognition, it is critical to improve the quality of the raw images acquired. Nowadays all images are affected by different factors that hinder the achievement of optimal image quality, making digital image processing a fundamental step prior to the application of any other practical application. The most common of these factors are noise and poor acquisition conditions: noise artefacts hamper proper image interpretation of the image; and acquisition in poor lighting or exposure conditions, such as dynamic scenes, causes loss of image information that can be key for certain processing tasks. Image (pre-) processing steps known as smoothing and sharpening are commonly applied to overcome these inconveniences: Smoothing is aimed at reducing noise and sharpening at improving or recovering imprecise or damaged information of image details and edges with insufficient sharpness or blurred content that prevents optimal image (post-)processing. There are many methods for smoothing the noise in an image, however in many cases the filtering process causes blurring at the edges and details of the image. Besides, there are also many sharpening techniques, which try to combat the loss of information due to blurring of image texture and need to contemplate the existence of noise in the image they process. When dealing with a noisy image, any sharpening technique may amplify the noise. Although the intuitive idea to solve this last case would be the previous filtering and later sharpening, this approach has proved not to be optimal: the filtering could remove information that, in turn, may not be recoverable in the later sharpening step. In the present PhD dissertation we propose a model based on graph theory for color image processing from a vector approach. In this model, a graph is built for each pixel in such a way that its features allow to characterize and classify the pixel. As we will show, the model we proposed is robust and versatile: potentially able to adapt to a variety of applications. In particular, we apply the model to create new solutions for the two fundamentals problems in image processing: smoothing and sharpening. To approach high performance image smoothing we use the proposed model to determine if a pixel belongs to a at region or not, taking into account the need to achieve a high-precision classification even in the presence of noise. Thus, we build an adaptive soft-switching filter by employing the pixel classification to combine the outputs from a filter with high smoothing capability and a softer one to smooth edge/detail regions. Further, another application of our model allows to use pixels characterization to successfully perform a simultaneous smoothing and sharpening of color images. In this way, we address one of the classical challenges within the image processing field. We compare all the image processing techniques proposed with other state-of-the-art methods to show that they are competitive both from an objective (numerical) and visual evaluation point of view. / Pérez Benito, C. (2019). Color Image Processing based on Graph Theory [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/123955 / TESIS

No description available.

A generic conflict model is developed to analyze international toxic waste disposal issues, and then, to provide feasible strategic resolutions for this serious environmental dispute. With the rapid growth of the global economy, toxic waste traffic from the advanced to developing nations has become a serious side effect of this globalization. The illegal transboundary movement of toxic wastes not only aggravates the burden on the poorer nations, but also negatively impacts the worldwide environment. In this thesis, the ongoing toxic waste disputes are divided into two stages consisting of the dumping prevention and dispute resolution stages. The analyses based on the methodology of Graph Model for Conflict Resolution are used in both stages in order to grasp the structure and implications of the conflict from a strategic viewpoint. The in-depth modeling of the toxic waste dumping disputes, which consist of historical and generic situations, specifies the involved parties and their options. By synthesizing the economic, political and legal factors, the relative preferences for each party can be determined. The Graphical User Interface (GUI) of the Decision Support System (DSS) GMCR II simplifies the processing of calculations. The analytical research furnishes investigators or other interested parties with possible resolutions for the disputes arising from an international waste dumping event. Sensitivity analyses are also conducted to provide a comprehensive understanding of the different situations that may occur in real-world cases. The case study of the Ivory Coast waste dumping controversy is used to demonstrate how to practically implement the generic multi-stage graph model.

A generic conflict model is developed to analyze international toxic waste disposal issues, and then, to provide feasible strategic resolutions for this serious environmental dispute. With the rapid growth of the global economy, toxic waste traffic from the advanced to developing nations has become a serious side effect of this globalization. The illegal transboundary movement of toxic wastes not only aggravates the burden on the poorer nations, but also negatively impacts the worldwide environment. In this thesis, the ongoing toxic waste disputes are divided into two stages consisting of the dumping prevention and dispute resolution stages. The analyses based on the methodology of Graph Model for Conflict Resolution are used in both stages in order to grasp the structure and implications of the conflict from a strategic viewpoint. The in-depth modeling of the toxic waste dumping disputes, which consist of historical and generic situations, specifies the involved parties and their options. By synthesizing the economic, political and legal factors, the relative preferences for each party can be determined. The Graphical User Interface (GUI) of the Decision Support System (DSS) GMCR II simplifies the processing of calculations. The analytical research furnishes investigators or other interested parties with possible resolutions for the disputes arising from an international waste dumping event. Sensitivity analyses are also conducted to provide a comprehensive understanding of the different situations that may occur in real-world cases. The case study of the Ivory Coast waste dumping controversy is used to demonstrate how to practically implement the generic multi-stage graph model.

A Fuzzy Preference Framework for the Graph Model for Conflict Resolution (FGM) is developed so that real-world conflicts in which decision makers (DMs) have uncertain preferences can be modeled and analyzed mathematically in order to gain strategic insights. The graph model methodology constitutes both a formal representation of a multiple participant-multiple objective decision problem and a set of analysis procedures that provide insights into them. Because crisp or definite preference is a special case of fuzzy preference, the new framework of the graph model can include---and integrate into the analysis---both certain and uncertain information about DMs' preferences. In this sense, the FGM is an important generalization of the existing graph model for conflict resolution. One key contribution of this study is to extend the four basic graph model stability definitions to models with fuzzy preferences. Together, fuzzy Nash stability, fuzzy general metarationality, fuzzy symmetric metarationality, and fuzzy sequential stability provide a realistic description of human behavior under conflict in the face of uncertainty. A state is fuzzy stable for a DM if a move to any other state is not sufficiently likely to yield an outcome the DM prefers, where sufficiency is measured according to a fuzzy satisficing threshold that is characteristic of the DM. A fuzzy equilibrium, an outcome that is fuzzy stable for all DMs, therefore represents a possible resolution of the conflict. To demonstrate their applicability, the fuzzy stability definitions are applied to a generic two-DM sustainable development conflict, in which a developer plans to build or operate a project inspected by an environmental agency. This application identifies stable outcomes, and thus clarifies the necessary conditions for sustainability. The methodology is then applied to an actual dispute with more than two DMs concerning groundwater contamination that took place in Elmira, Ontario, Canada, again uncovering valuable strategic insights. To investigate how DMs with fuzzy preferences can cooperate in a strategic conflict, coalition fuzzy stability concepts are developed within FGM. In particular, coalition fuzzy Nash stability, coalition fuzzy general metarationality, coalition fuzzy symmetric metarationality, and coalition fuzzy sequential stability are defined, for both a coalition and a single DM. These concepts constitute a natural generalization of the corresponding non-cooperative fuzzy preference-based definitions for Nash stability, general metarationality, symmetric metarationality, and sequential stability, respectively. As a follow-up analysis of the non-cooperative fuzzy stability results and to demonstrate their applicability, the coalition fuzzy stability definitions are applied to the aforementioned Elmira groundwater contamination conflict. These new concepts can be conveniently utilized in the study of practical problems in order to gain strategic insights and to compare conclusions derived from both cooperative and non-cooperative stability notions. A fuzzy option prioritization technique is developed within the FGM so that uncertain preferences of DMs in strategic conflicts can be efficiently modeled as fuzzy preferences by using the fuzzy truth values they assign to preference statements about feasible states. The preference statements of a DM express desirable combinations of options or courses of action, and are listed in order of importance. A fuzzy truth value is a truth degree, expressed as a number between 0 and 1, capturing uncertainty in the truth of a preference statement at a feasible state. It is established that the output of a fuzzy preference formula, developed based on the fuzzy truth values of preference statements, is always a fuzzy preference relation. The fuzzy option prioritization methodology can also be employed when the truth values of preference statements at feasible states are formally based on Boolean logic, thereby generating a crisp preference over feasible states that is the same as would be found using the existing crisp option prioritization approach. Therefore, crisp option prioritization is a special case of fuzzy option prioritization. To demonstrate how this methodology can be used to represent fuzzy preferences in real-world problems, the new fuzzy option prioritization technique is applied to the Elmira aquifer contamination conflict. It is observed that the fuzzy preferences obtained by employing this technique are very close to those found using the rather complicated and tedious pairwise comparison approach.

A Fuzzy Preference Framework for the Graph Model for Conflict Resolution (FGM) is developed so that real-world conflicts in which decision makers (DMs) have uncertain preferences can be modeled and analyzed mathematically in order to gain strategic insights. The graph model methodology constitutes both a formal representation of a multiple participant-multiple objective decision problem and a set of analysis procedures that provide insights into them. Because crisp or definite preference is a special case of fuzzy preference, the new framework of the graph model can include---and integrate into the analysis---both certain and uncertain information about DMs' preferences. In this sense, the FGM is an important generalization of the existing graph model for conflict resolution. One key contribution of this study is to extend the four basic graph model stability definitions to models with fuzzy preferences. Together, fuzzy Nash stability, fuzzy general metarationality, fuzzy symmetric metarationality, and fuzzy sequential stability provide a realistic description of human behavior under conflict in the face of uncertainty. A state is fuzzy stable for a DM if a move to any other state is not sufficiently likely to yield an outcome the DM prefers, where sufficiency is measured according to a fuzzy satisficing threshold that is characteristic of the DM. A fuzzy equilibrium, an outcome that is fuzzy stable for all DMs, therefore represents a possible resolution of the conflict. To demonstrate their applicability, the fuzzy stability definitions are applied to a generic two-DM sustainable development conflict, in which a developer plans to build or operate a project inspected by an environmental agency. This application identifies stable outcomes, and thus clarifies the necessary conditions for sustainability. The methodology is then applied to an actual dispute with more than two DMs concerning groundwater contamination that took place in Elmira, Ontario, Canada, again uncovering valuable strategic insights. To investigate how DMs with fuzzy preferences can cooperate in a strategic conflict, coalition fuzzy stability concepts are developed within FGM. In particular, coalition fuzzy Nash stability, coalition fuzzy general metarationality, coalition fuzzy symmetric metarationality, and coalition fuzzy sequential stability are defined, for both a coalition and a single DM. These concepts constitute a natural generalization of the corresponding non-cooperative fuzzy preference-based definitions for Nash stability, general metarationality, symmetric metarationality, and sequential stability, respectively. As a follow-up analysis of the non-cooperative fuzzy stability results and to demonstrate their applicability, the coalition fuzzy stability definitions are applied to the aforementioned Elmira groundwater contamination conflict. These new concepts can be conveniently utilized in the study of practical problems in order to gain strategic insights and to compare conclusions derived from both cooperative and non-cooperative stability notions. A fuzzy option prioritization technique is developed within the FGM so that uncertain preferences of DMs in strategic conflicts can be efficiently modeled as fuzzy preferences by using the fuzzy truth values they assign to preference statements about feasible states. The preference statements of a DM express desirable combinations of options or courses of action, and are listed in order of importance. A fuzzy truth value is a truth degree, expressed as a number between 0 and 1, capturing uncertainty in the truth of a preference statement at a feasible state. It is established that the output of a fuzzy preference formula, developed based on the fuzzy truth values of preference statements, is always a fuzzy preference relation. The fuzzy option prioritization methodology can also be employed when the truth values of preference statements at feasible states are formally based on Boolean logic, thereby generating a crisp preference over feasible states that is the same as would be found using the existing crisp option prioritization approach. Therefore, crisp option prioritization is a special case of fuzzy option prioritization. To demonstrate how this methodology can be used to represent fuzzy preferences in real-world problems, the new fuzzy option prioritization technique is applied to the Elmira aquifer contamination conflict. It is observed that the fuzzy preferences obtained by employing this technique are very close to those found using the rather complicated and tedious pairwise comparison approach.

A system of systems (SoS) framework is proposed for policy design that takes into account the value systems of multiple participants, harnesses the complexity of strategic interactions among participants, and confronts the risks and uncertainties present in participants’ decision making. SoS thinking provides an integrative and adaptive mindset, which is needed to tackle policy challenges characterized by conflict, complexity, and uncertainty. With the aim of putting SoS thinking into practice, operational methods and tools are presented herein. Specifically, SoS engineering methodologies to create value system models, agent-based models of competitive and cooperative behaviour under conflict, and risk management models are developed and integrated into the framework. The proposed structure, methods and tools can be utilized to organize policy design discourse. Communication among participants involved in the policy discussion is structured around SoS models, which are used to integrate multiple perspectives of a system and to test the effectiveness of policies in achieving desirable outcomes under varying conditions. In order to demonstrate the proposed methods and tools that have been developed to enliven policy design discourse, a theoretical common-pool resources dilemma is utilized. The generic application illustrates the methodology of constructing ordinal preferences from values. Also, it is used to validate the agent-based modeling and simulation platform as a tool to investigate strategic interactions among participants and harness the potential to influence and enable participants to achieve desirable outcomes. A real-world common pool resources dilemma in the provisioning and security considerations of the Straits of Malacca and Singapore is examined and employed as a case study for applying strategic conflict models in risk management. Overall, this thesis advances the theory and application of SoS engineering and focuses on understanding value systems, handling complexity in terms of conflict dynamics, and finally, enhancing risk management.

A system of systems (SoS) framework is proposed for policy design that takes into account the value systems of multiple participants, harnesses the complexity of strategic interactions among participants, and confronts the risks and uncertainties present in participants’ decision making. SoS thinking provides an integrative and adaptive mindset, which is needed to tackle policy challenges characterized by conflict, complexity, and uncertainty. With the aim of putting SoS thinking into practice, operational methods and tools are presented herein. Specifically, SoS engineering methodologies to create value system models, agent-based models of competitive and cooperative behaviour under conflict, and risk management models are developed and integrated into the framework. The proposed structure, methods and tools can be utilized to organize policy design discourse. Communication among participants involved in the policy discussion is structured around SoS models, which are used to integrate multiple perspectives of a system and to test the effectiveness of policies in achieving desirable outcomes under varying conditions. In order to demonstrate the proposed methods and tools that have been developed to enliven policy design discourse, a theoretical common-pool resources dilemma is utilized. The generic application illustrates the methodology of constructing ordinal preferences from values. Also, it is used to validate the agent-based modeling and simulation platform as a tool to investigate strategic interactions among participants and harness the potential to influence and enable participants to achieve desirable outcomes. A real-world common pool resources dilemma in the provisioning and security considerations of the Straits of Malacca and Singapore is examined and employed as a case study for applying strategic conflict models in risk management. Overall, this thesis advances the theory and application of SoS engineering and focuses on understanding value systems, handling complexity in terms of conflict dynamics, and finally, enhancing risk management.