Suchergebnisse

Politicas públicas de água têm grande influência sobre diferentes tipos de recursos (recursos hídricos, da terra e do solo; infraestrutura e instalações prediais; recursos financeiros; informação e conhecimento ambiental; etc.). Elas atuam sobre agentes individuais ou coletivos (usuários, gestores, empresas públicas ou privadas, associações, etc.), assim como como regras e normas de comportamento que estes atores são os destinatários ou agentes. Sistemas complexos, se for o caso, essas políticas têm vários tipos de efeitos, esperados e inesperados, os efeitos diretos e indiretos, sociais, econômicos, ambientais e ecosistêmica. O atual desenvolvimento de plataformas multi-agente abre uma nova área para a definição, concepção, implementação e monitoramento da gestão da água, produzindo simulações ex ante do impacto das medidas que promovem políticas públicas de água e da evolução provável da situação sócio--HYDROSYSTEM em causa. Aqui vamos dar uma visão geral das novas oportunidades de modelagem de política da água e avaliação de impacto, que resumem as etapas do processo de modelagem e apresentar os principais ingredientes que entram na composição de uma plataforma dedicada a simulações de impacto. Também argumentam que o interesse de construir cenários de água e produção de indicadores úteis para a tomada de decisão sobre o uso, distribuição e gestão dos recursos hídricos à escala da bacia. ; Water policies have a great impact upon different types of resources (water, land and soil resour-ces; infrastructure and facilities; financial resour-ces; environmental knowledge and information; etc.). They involve many individual or collective actors (users, managers, public or private companies, associations, etc.) as well as rules and norms of behavior that these actors are the reci-pients or agents. Complex systems, if any, these policies have several kinds of effects, expected and unexpected, direct and indirect effects, societal, economic, environmental and eco-systemic. The current development of multi-agent platforms opens up a new area for the definition, design, implementation and monitoring of water management by producing ex ante simulations of the impact of measures that promote water public policies and of the likely evolution of the socio-hydrosystem concerned. Here we give a quick overview of these new opportunities of water policy modeling and impact assessment. We summarize the steps of the modeling process and present the main ingredients entering in the composition of a platform dedicated to impact simulations. We also argue the interest of building water scenarios and producing useful indicators for decision-making regarding the use, distribu-tion and management of water resources at the basin-scale.

Simulation is an important tool for prediction and assessment of the behavior of complex systems and situations. The importance of simulation has increased tremendously during the last few decades, mainly because the rapid pace of development in the field of electronics has turned the computer from a costly and obscure piece of equipment to a cheap ubiquitous tool which is now an integral part of our daily lives. While such technological improvements make it easier to analyze well-understood deterministic systems, increase in speed and storage capacity alone are not enough when simulating situations where human beings and their behavior are an integral part of the system being studied. The problem with simulation of intelligent entities is that intelligence is still not well understood and it seems that the field of Artificial Intelligence (AI) has a long way to go before we get computers to think like humans. Behavior-based agent modeling has been proposed in mid-80's as one of the alternatives to the classical AI approach. While used mainly for the control of specialized robotic vehicles with very specific sensory capabilities and limited intelligence, we believe that a behavior-based approach to modeling generic autonomous agents in complex environments can provide promising results. To this end, we are investigating a behavior-based model for controlling groups of collaborating and competing agents in a geographic terrain. In this thesis, we are focusing on scenarios of military nature, where agents can move within the environment and adversaries can eliminate each other through use of weapons. Different aspects of agent behavior like navigation to a goal or staying in group formation, are implemented by distinct behavior modules and the final observed behavior for each agent is an emergent property of the combination of simple behaviors and their interaction with the environment. Our experiments show that while such an approach is quite efficient in terms of computational power, it has some major drawbacks. One of the problems is that reactive behavior-based navigation algorithms are not well suited for environments with complex mobility constraints where they tend to perform much worse than proper path planning. This problem represents an important research question, especially when it is considered that most of the modern military conflicts and operations occur in urban environments. One of the contributions of this thesis is a novel approach to reactive navigation where goals and terrain information are fused based on the idea of transforming a terrain with obstacles into a virtual obstacle-free terrain. Experimental results show that our approach can successfully combine the low run-time computational complexity of reactive methods with the high success rates of classical path planning. Another interesting research problem is how to deal with the unpredictable nature of emergent behavior. It is not uncommon to have situations where an outcome diverges significantly from the intended behavior of the agents due to highly complex nonlinear interactions with other agents or the environment itself. Chances of devising a formal way to predict and avoid such abnormalities are slim at best, mostly because such complex systems tend to be be chaotic in nature. Instead, we focus on detection of deviations through tracking group behavior which is a key component of the total situation awareness capability required by modern technology-oriented and network-centric warfare. We have designed a simple and efficient clustering algorithm for tracking of groups of agent suitable for both spatial and behavioral domain. We also show how to detect certain events of interest based on a temporal analysis of the evolution of discovered clusters. ; 2006-12-01 ; Ph.D. ; Engineering and Computer Science, School of Electrical Engineering and Computer Science ; Doctorate ; This record was generated from author submitted information.

Farmland is the most basic material condition for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both stable rural livelihoods and sustainable farmland use into account has vital significance in theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems, and natural and social factors that are related to its changing process need to be considered when modeling farmland changing processes. This paper uses Qianjingou Town in the Inner Mongolian farming–pastoral zone as a study area. From the perspective of the relationship between household livelihood and farmland use, this study establishes the process mechanism of farmland use change based on questionnaire data, and constructs a multi-agent simulation model of farmland use change using the Eclipse and Repast toolbox. Through simulating the relationship between natural factors (including geographical location) and household behavior, this paper systematically simulates household farmland abandonment and rent behaviors, and accurately describes the dynamic interactions between household livelihoods and the factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (household family structures, economic development and government policies). Ultimately, this study scientifically predicts the future farmland use change trend in the next 30 years. The simulation results show that the number of abandoned and sublet farmland plots has a gradually increasing trend, and the number of non-farming households and pure-outworking households has a remarkable increasing trend, whereas the number of part-farming households and pure-farming households has a decreasing trend. Household livelihood sustainability in the study area is confronted with increasing pressure, and household non-farm employment has an increasing trend, while regional appropriate-scale agricultural management is maintained. The research results establish the theoretical foundation and a basic method for developing sustainable farmland use management that can meet the willingness of households and guarantee grain and ecological security.

The article is devoted to the analysis of existing experience in the application of agent-based approach by modeling migration processes carried out for ongoing development of complex agent-based models to simulate processes in the field of migration policy. Analysis showed that despite the advantages demonstrated by the agent-based approach compared with traditional methods of demographic research simulation reveals various difficulties in terms of simulating migration processes that nevertheless do not underestimate advantages of agent and other existing modeling approaches. Hybrid population-based agent modeling is a new emerging field of study that showed advantages by implementing this approach. The explosive population growth around the world over the past few decades has had an enormous impact on the level of natural resources, the state of the environment and the structure of society in many countries. The study of demographic and migratory trends and the dynamics of changes in the population structure plays a key role in the formation of domestic as well as global policies to achieve sustainable social and environmental development.

"Agent-Based Modeling in Political Decision Making" published on by Oxford University Press.