A game-theoretic network formation model

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

La gouvernance des réseaux de politique publique : le cas du programme VIH en Haïti

Cette thèse concerne la gouvernance des réseaux de politique publique. Elle cherche à mieux comprendre le phénomène par l’analyse des caractéristiques du réseau d’acteurs impliqués, les défis qui se posent relativement au processus de gouverne, et l’influence qui en résulte pour les interventions. Le cadre d’analyse s’appuie essentiellement sur deux théories de la sociologie des organisations, en l’occurrence la théorie de l’acteur stratégique (Crozier et Friedberg 1977), et la théorie des réseaux de politique publique (Rhodes 1997). Il s’agit d’une étude de cas portant sur le programme VIH/Sida en Haïti, celui-ci étant documenté à partir de données d’entretiens, d’observations et de groupes de discussion. Les résultats de la recherche sont structurés en quatre articles. Le premier article rend compte de l’étape préliminaire, mais non moins importante, de la recherche, c’est-à-dire le travail de terrain. Il présente les défis méthodologiques et éthiques inhérents à la rencontre entre chercheur et participants pour la coconstruction des savoirs, notamment dans le contexte de la recherche en santé mondiale. Le deuxième article analyse les caractéristiques du réseau d’acteurs et montre la nécessité de prendre en compte les attributs propres des acteurs en plus de la structure de leurs interactions pour comprendre la gouvernance des réseaux de politique publique. La plupart des analyses, surtout celles s’appuyant sur l’approche réseau, cherchent à comprendre comment la structure des relations entre les acteurs influence la gouverne, le contenu ou les résultats de politiques. Or, dans le cas du programme VIH en Haïti, il apparaît que ce sont en réalité les attributs des acteurs en termes de ressources et de pouvoir, qui orientent leurs interactions avec les autres acteurs. Le troisième article présente un cadre d’analyse et illustre, à partir de celui-ci, l’influence des outils et des structures, ainsi que du contexte sociopolitique et économique sur la gouvernance du programme VIH/Sida en Haïti. Il argumente ensuite sur les défis que cela pose à la coordination des interventions et à la mise en place des relations de partenariat au sein du réseau d’acteurs. Le quatrième article se penche sur l’émergence de besoins nouveaux chez les personnes vivant avec le VIH (PVVIH) et met en lumière la faiblesse des processus de planification à les cibler. Il renouvelle l’intérêt de l’approche participative, notamment dans le contexte des pays en développement, où il devient crucial d’adapter les interventions au contexte local en utilisant le potentiel et les ressources des communautés. L’étude a donc permis de montrer : 1) les liens qui existent entre les attributs des acteurs, la configuration particulière de leurs interactions et le processus de gouverne; 2) les défis qui résultent de l’influence des outils et structures mis en place, ainsi que des facteurs socioéconomiques et politiques sur le processus de gouverne, et enfin; 3) le lien qui existe entre le mode de gouvernance – via la participation - et la prise en compte des besoins émergents des PVVIH.

Les réseaux militaires comme acteurs des relations internationales : le cas du Multinational Interoperability Council

Depuis plus de cinquante ans, les puissances occidentales ont créé toutes sortes de réseaux militaires internationaux, afin de renforcer leurs liens et harmoniser leurs techniques, leurs équipements et leurs façons de faire. Jusqu’à ce jour, ces regroupements sont demeurés largement ignorés de la discipline des relations internationales. Or, la mondialisation des échanges et l’essor des technologies de l’information ont ouvert les processus politiques à de nouveaux acteurs, y compris en matière de sécurité, jetant un éclairage nouveau sur le rôle, la mission et les responsabilités que les États délèguent à ces réseaux. En menant une analyse approfondie d’un réseau militaire, le Multinational Interoperability Council, cette recherche a pour objectifs de définir les réseaux militaires internationaux en tant que catégorie d’analyse des relations internationales, de documenter empiriquement leur fonctionnement et de mieux comprendre leur rôle dans le champ de la sécurité internationale. Pour ce faire, la démarche propose de recourir à l’appareil conceptuel de l’institutionnalisme relationnel, de la théorie des champs et du tournant pratiques en relations internationales. Cette combinaison permet d’aborder les dimensions institutionnelle, cognitive et pratique de l’action collective au sein du réseau étudié. L’analyse nous apprend que, malgré une influence limitée, le MIC produit une identité, des capacités, des préférences et des effets qui lui sont propres. Les acteurs du MIC ont eux-mêmes généré certaines conditions de son institutionnalisation, et sont parvenus à faire du réseau, d’abord conçu comme une structure d’échanges d’informations, un acteur intentionnel du champ de la sécurité internationale. Le MIC ne peut agir de façon autonome, sans contrôle des États. Cependant, les relations établies entre les militaires qui y participent leur offrent des capacités – le capital social, politique et d’expertise – dont ils ne disposeraient pas autrement, et qu’ils peuvent mobiliser dans leurs interactions avec les autres acteurs du champ.

Introduction to Network Mathematics

Introduction to Network Mathematics provides college students with basic graph theory to better understand the Internet

On social networks and game theory, some research problems

Seminar given as part of social networking course, to give a brief overview of some applied examples game theory used in social network simulation

"Thematically Analysing Social Network Content During Disasters Through the Lens of the Disaster Management Lifecycle" & "Investigating Similarity Between Privacy Policies of Social Networking Sites as a Precursor for Standardization"

Abstract 1: Social Networks such as Twitter are often used for disseminating and collecting information during natural disasters. The potential for its use in Disaster Management has been acknowledged. However, more nuanced understanding of the communications that take place on social networks are required to more effectively integrate this information into the processes within disaster management. The type and value of information shared should be assessed, determining the benefits and issues, with credibility and reliability as known concerns. Mapping the tweets in relation to the modelled stages of a disaster can be a useful evaluation for determining the benefits/drawbacks of using data from social networks, such as Twitter, in disaster management.A thematic analysis of tweets’ content, language and tone during the UK Storms and Floods 2013/14 was conducted. Manual scripting was used to determine the official sequence of events, and classify the stages of the disaster into the phases of the Disaster Management Lifecycle, to produce a timeline. Twenty- five topics discussed on Twitter emerged, and three key types of tweets, based on the language and tone, were identified. The timeline represents the events of the disaster, according to the Met Office reports, classed into B. Faulkner’s Disaster Management Lifecycle framework. Context is provided when observing the analysed tweets against the timeline. This illustrates a potential basis and benefit for mapping tweets into the Disaster Management Lifecycle phases. Comparing the number of tweets submitted in each month with the timeline, suggests users tweet more as an event heightens and persists. Furthermore, users generally express greater emotion and urgency in their tweets.This paper concludes that the thematic analysis of content on social networks, such as Twitter, can be useful in gaining additional perspectives for disaster management. It demonstrates that mapping tweets into the phases of a Disaster Management Lifecycle model can have benefits in the recovery phase, not just in the response phase, to potentially improve future policies and activities. Abstract2: The current execution of privacy policies, as a mode of communicating information to users, is unsatisfactory. Social networking sites (SNS) exemplify this issue, attracting growing concerns regarding their use of personal data and its effect on user privacy. This demonstrates the need for more informative policies. However, SNS lack the incentives required to improve policies, which is exacerbated by the difficulties of creating a policy that is both concise and compliant. Standardization addresses many of these issues, providing benefits for users and SNS, although it is only possible if policies share attributes which can be standardized. This investigation used thematic analysis and cross- document structure theory, to assess the similarity of attributes between the privacy policies (as available in August 2014), of the six most frequently visited SNS globally. Using the Jaccard similarity coefficient, two types of attribute were measured; the clauses used by SNS and the coverage of forty recommendations made by the UK Information Commissioner’s Office. Analysis showed that whilst similarity in the clauses used was low, similarity in the recommendations covered was high, indicating that SNS use different clauses, but to convey similar information. The analysis also showed that low similarity in the clauses was largely due to differences in semantics, elaboration and functionality between SNS. Therefore, this paper proposes that the policies of SNS already share attributes, indicating the feasibility of standardization and five recommendations are made to begin facilitating this, based on the findings of the investigation.

Incidencia de las agresiones a la seguridad cibernética en el desarrollo informático de las Fuerzas Armadas de Estados Unidos (2003-2013)

La presente investigación tiene como objetivo analizar la incidencia de las agresiones cibernéticas en el desarrollo informático de las Fuerzas Armadas de Estados Unidos. Los diferentes estudios que se han realizado sobre el ciberespacio se han enfocado en el papel del individuo como actor principal y se ha dejado de lado las repercusiones que éste ha tenido para el Estado, como un nuevo eje de amenazas. Teniendo en cuenta lo anterior, esta investigación demostrará a partir del concepto de securitización, que se busca priorizar la “ciberseguridad” dentro de la agenda del gobierno estadounidense. Al ser este un estudio que aborda experiencias concretas durante un periodo de tiempo de más de 10 años, el diseño metodológico de la investigación será longitudinal, ya que abarcará estudios, artículos, textos y resoluciones que se han realizado desde 2003 hasta la actualidad.

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role is to provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Innovative approach to building systems integration problems: Using systems theory, technological forecasting and scenario planning

Building services are worth about 2% GDP and are essential for the effective and efficient operations of the building. It is increasingly recognised that the value of a building is related to the way it supports the client organisation’s ongoing business operations. Building services are central to the functional performance of buildings and provide the necessary conditions for health, well-being, safety and security of the occupants. They frequently comprise several technologically distinct sub-systems and their design and construction requires the involvement of numerous disciplines and trades. Designers and contractors working on the same project are frequently employed by different companies. Materials and equipment is supplied by a diverse range of manufacturers. Facilities managers are responsible for operation of the building service in use. The coordination between these participants is crucially important to achieve optimum performance, but too often is neglected. This leaves room for serious faults. The need for effective integration is important. Modern technology offers increasing opportunities for integrated personal-control systems for lighting, ventilation and security as well as interoperability between systems. Opportunities for a new mode of systems integration are provided by the emergence of PFI/PPP procurements frameworks. This paper attempts to establish how systems integration can be achieved in the process of designing, constructing and operating building services. The essence of the paper therefore is to envisage the emergent organisational responses to the realisation of building services as an interactive systems network.

Future directions for child anxiety theory and treatment

The aim of this introductory paper, and of this special issue of Cognition and Emotion, is to stimulate debate about theoretical issues that will inform child anxiety research in the coming years. Papers included in this special issue have arisen from an Economic and Social Research Council (ESRC, UK) funded seminar series, which we called Child Anxiety Theory and Treatment (CATTS). We begin with an overview of the CATTS project before discussing (1) the application of adult models of anxiety to children, and (2) the role of parents in child anxiety. We explore the utility of adult models of anxiety for child populations before discussing the problems that are associated with employing them uncritically in this context. The study of anxiety in children provides the opportunity to observe the trajectory of anxiety and to identify variables that causally influence its development. Parental influences are of particular interest and new and imaginative strategies are required to isolate the complex network of causal relationships therein. We conclude by suggesting that research into the causes and developmental course of anxiety in children should be developed further. We also propose that, although much is known about the role of parents in the development of anxiety, it would be useful for research in this area to move towards an examination of the specific processes involved. We hope that these views represent a constructive agenda for people in the field to consider when planning future research.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Modified radial basis function neural network using output transformation

A modified radial basis function (RBF) neural network and its identification algorithm based on observational data with heterogeneous noise are introduced. The transformed system output of Box-Cox is represented by the RBF neural network. To identify the model from observational data, the singular value decomposition of the full regression matrix consisting of basis functions formed by system input data is initially carried out and a new fast identification method is then developed using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator (MLE) for a model base spanned by the largest eigenvectors. Finally, the Box-Cox transformation-based RBF neural network, with good generalisation and sparsity, is identified based on the derived optimal Box-Cox transformation and an orthogonal forward regression algorithm using a pseudo-PRESS statistic to select a sparse RBF model with good generalisation. The proposed algorithm and its efficacy are demonstrated with numerical examples.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

Dynamic recurrent neural network for system identification and control

A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.

Neurofuzzy mixture of experts network parallel learning and model construction algorithms

A connection between a fuzzy neural network model with the mixture of experts network (MEN) modelling approach is established. Based on this linkage, two new neuro-fuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems.