Parallel simulation of large population dynamics

Agent-based modeling and simulation is a promising methodology that can be used in the study of population dynamics. We present the design and development of a simulation tool which provides basic support for modeling and simulating agent-based demographic systems. Our results prove that agent-based modeling can work effectively in the study of demographic scenarios which can help to better policy planning and analysis. Moreover, parallel environment looks suitable for the study of large-scale individual-based simulations of this kind.Postprint (published version

Approaching simulation to modelers: a user interface for large-scale demographic simulation

Extended version / Versió extesaAgent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models such as policy studies, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.Postprint (author's final draft

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)

In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.Agent-Based Modeling, Survey, Current Practices, Simulation Validation, Simulation Purpose

Self Organized Dynamic Tree Neural Network

Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partitional, hierarchical, density studies, probabilistic, etc. This article will present the SODTNN, which can perform clustering by integrating hierarchical and density-based methods. The network incorporates the behavior of self-organizing maps and does not specify the number of existing clusters in order to create the various groups

Modelado y simulación de la evolución de valores en sociedades humanas con agentes software

El proyecto aborda, desde una perspectiva multidisciplinar, la integración de métodos y herramientas de los campos de la ingeniería del software, la inteligencia artificial y la sociología. Así, se pretende simular la complejidad de las sociedades humanas desde el diseño de un modelo sociológico. Este modelo tratará de simplificar la realidad extrayendo las características relevantes para el problema objeto de estudio. La simulación social implementará, según las líneas establecidas por dicho modelo, un sistema multiagente en un entorno cerrado. La evaluación del sistema se realizará comparando sus resultados con los datos extraídos de encuestas reales. Se ha experimentado también con otras técnicas de inteligencia artificial, obteniendo distintos módulos de ampliación del sistema: lógica borrosa y salida en lenguaje natural. Esta memoria se complementa con los artículos realizados sobre este proyecto, que se adjuntan al final de la misma

A framework to study the resilience of organizations: a case study of a nuclear emergency plan

El desarrollo de la resiliencia es un campo de investigación importante en ámbitos como el Management, la Ingeniería, la Psicología o la Ecología. La importancia del estudio de la resiliencia se ha visto desarrollada por el aumento tanto de desastres naturales como antropogénicos, así como por el desarrollo de conciencia acerca de sus efectos. Estas razones de peso han influido en que los Gobiernos estén invirtiendo recursos en la mejora de la resiliencia de organizaciones, infraestructuras, ciudades, individuos, etc. Sin embargo, a pesar de su importancia, el número de trabajos de investigación que se centran en el desarrollo de metodologías específicas para el diseño de organizaciones resilientes es reducido. El principal objetivo de esta investigación es mejorar este aspecto introduciendo un marco para el diseño de organizaciones resilientes. Para alcanzar este objetivo, se explica cómo emplear el Modelo de Sistemas Viables para el diseño de estas organizaciones. Nos hemos centrado en uno de los aspectos clave de la resiliencia: las comunicaciones. Para ello, se ha usado el caso de estudio del plan de emergencia de una central nuclear en España. Las comunicaciones en una organización pueden modelarse como un proceso de difusión en redes multiplex. Buscamos arquitecturas aplicables a nuestro caso de estudio. Sin embargo, no se ha encontrado ninguna que cumpliera con los requisitos que se necesitaban. Este hecho, nos ha llevado a proponer una nueva arquitectura, que además de permitir estudiar la difusión de información en una organización, permite estudiar otros procesos de difusión en redes multiplex.Departamento de Organización de Empresas y Comercialización e Investigación de MercadosDoctorado en Ingeniería Industria

Competition and collaboration in supply chains: an agent-based modelling approach

Competition has been considered as an effective means to improve business and economic competitiveness. However, competition in supply chain management (SCM) can be viewed as a source of uncertainty. Most recommended collaboration strategies in SCM literature tend to avoid the emergence of competition inside the supply chain, but, in reality, these strategies do not lead all supply chains to success. In addition, from strategic management perspective, these collaboration strategies are not believed to encourage firms to improve their performance. Both competition and collaboration are critical issues in achieving business success, but the effect of both factors on the market has not been explored concurrently in the literature. The complexity of this issue should be investigated using a comprehensive perspective, and it is hard to undertake by using an empirical approach. [Continues.

Identification of Influentials in virtual social network: an agent-based simulation model of social influence processes

Die zunehmende Virtualisierung von gesellschaftlichen Sozialstrukturen durch den Social Media Bereich und insbesondere durch die virtuellen sozialen Netzwerke stellt die Marketingforschung vor neue Herausforderungen. Aufgrund der technologischen Entwicklung des Web 2.0 entstehen für Konsumenten schnelle und einfache Kommunikations- und Interaktionsmöglichkeiten zum Erfahrungsaustausch über die Produkte und Dienstleistungen eines Unternehmens. Innerhalb eines virtuellen sozialen Netzwerkes existieren Influentials, die aufgrund ihrer kommunikativen Verhaltensweisen und der netzwerkstrukturellen Einbettung eine einzigartige soziale Beeinflussungsfähigkeit aufweisen. Für das Marketing der Unternehmen stellen das Verständnis über die sozialen Beeinflussungsprozesse und die Identifikation der Influentials die zentralen Erfolgsfaktoren dar, um die Konsumenteninteraktion im Sinne der Unternehmenszielsetzung zu beeinflussen. Bisherige Analyse- bzw. Identifikationsmethoden für diese Influentials vernachlässigen jedoch die bedeutsame interpersonelle Perspektive. Die netzwerkstrukturelle Einbettung der Konsumenten bzw. Individuen sowie deren Kommunikations- und Interaktionsprozesse untereinander führen zu einem dynamischen, nichtlinearen und komplexen Sozialsystem. Bei der Untersuchung dieser Dynamiken stoßen traditionelle Analysemethoden der Marketingforschung an ihre Grenzen. Deshalb entwickelt der Verfasser ein agentenbasiertes Simulationsmodell, um das individuelle Konsumentenhalten als komplexes und dynamisches System abzubilden. Die Simulationsergebnisse deuten darauf hin, dass die Influentials weder über eine strukturell besonders bedeutsame Position innerhalb des Netzwerkes verfügen, noch eine erhöhte soziale Aktivität aufweisen. Die bisher verwendeten Verfahren der strukturellen sozialen Netzwerkanalyse und der sozialen Aktivitätsanalyse sind deshalb nur eingeschränkt zur Identifikation von Influentials geeignet. Aus einer interpersonellen Analyseperspektive zeigt sich, dass die Influentials eine besonders hohe wahrgenommene Glaubwürdigkeit aufweisen und das soziale Umfeld dieser Individuen durch eine hohe Empfänglichkeit für soziale Beeinflussungen gekennzeichnet ist. Die agentenbasierte Simulation erweitert somit das Verständnis über das sozial beeinflusste Konsumentenverhalten und liefert damit wertvolle Hinweise für die praxisnahe Identifikation von Influentials in einem virtuellen sozialen Netzwerk.Virtual social networking sites have become more and more popular over the last few years, attract millions of users worldwide and are growing exponentially. The increasing amount of virtually connected consumers leads to a social-driven information exchange about products, brands or services. Within virtual social networks, influentials can be considered as key users with high influence capabilities, unique communication patterns and important structural network positions. For marketers an understanding of social influence is key to benefit from consumer-to-consumer interaction and to address potential new customers by utilizing these influentials. So far, virtual social network analysis neglects interpersonal factors of influence as well as an individual consumer decision making perspective. The analysis of individual interaction and the lack of empirical data from virtual social networks require a research method, which models individual consumer behaviors as a complex and adaptive system. Therefore, the author develops an agent-based simulation model to explore and to investigate social influence processes by integrating perceived social activity, perceived structural positions and interpersonal relationship characteristics with an individual decision making perspective. Simulation results indicate that important members in virtual social networks are inadequately identified either through structural network or activity analysis respectively. Hence, these methods are less appropriate to identify influentials within a virtual social network. The interpersonal analysis of the social influence processes shows that influentials are characterized by a high perceived credibility. Moreover, the social contacts of the influentials are highly susceptible for social influences. The agent-based simulation model provides a deeper understanding of social influence processes in virtual social networks and serves marketers as a superior opportunity for identifying socially influential network members