Suchergebnisse

Asylum-related migration is highly complex, uncertain, and volatile, which precludes using standard model-based predictions to inform policy and operational decisions. At the same time, asylum's potentially high societal impacts on receiving countries and the resource implications of asylum processes call for more proactive approaches for assessing current and future migration flows. In this article, we propose an alternative approach to asylum modeling, based on the detection of early warning signals by using models originating from statistical control theory. Our empirical analysis of several asylum flows into Europe in 2010–2016 demonstrates the approach's utility and potential in aiding the management of mixed migration flows, while also shedding more light on the work needed to make better use of the "big data" and scenario-based methods for comprehensive and systematic examination of risk, uncertainty, and emerging trends.

Intro -- Foreword -- References -- Acknowledgements -- Contents -- Acronyms -- Part I Agent-Based Models -- 1 Introduction -- 1.1 Overview -- 1.2 Artificial Life as Digital Biology -- 1.2.1 Artificial Life as Empirical Data-Point -- 1.3 Social Simulation and Sociological Relevance -- 1.3.1 Methodological Concerns in Social Simulation -- 1.4 Case Study: Schelling's Residential Segregation Model -- 1.4.1 Implications of Schelling's Model -- 1.5 Social Simulation in Application: The Case of Demography -- 1.5.1 Building Model-Based Demography -- 1.6 General Summary -- 1.6.1 Alife Modelling -- 1.6.2 Simulation for the Social Sciences -- 1.6.3 Schelling's Model as a Case Study in Modelling -- 1.6.4 Developing a Model-Based Demography -- 1.6.5 General Conclusions of the Text: Messages for the Modeller -- 1.6.6 Chapter Summaries -- 1.6.7 Contributions -- References -- 2 Simulation and Artificial Life -- 2.1 Overview -- 2.2 Introduction to Simulation Methodology -- 2.2.1 The Goals of Scientific Modelling -- 2.2.2 Mathematical Models -- 2.2.3 Computational Models -- 2.2.4 The Science Versus Engineering Distinction -- 2.2.5 Connectionism: Scientific Modelling in Psychology -- 2.2.6 Bottom-Up Modelling and Emergence -- 2.3 Evolutionary Simulation Models and Artificial Life -- 2.3.1 Genetic Algorithms and Genetic Programming -- 2.3.2 Evolutionary Simulations and Artificial Life -- 2.3.3 Bedau and the Challenges Facing ALife -- 2.4 Truth in Simulation: The Validation Problem -- 2.4.1 Validation and Verification in Simulation -- 2.4.2 The Validation Process in Engineering Simulations -- 2.4.3 Validation in Scientific Simulations: Concepts of Truth -- 2.4.4 Validation in Scientific Models: Kuppers and Lenhard Case Study -- 2.5 The Connection Between Theory and Simulation -- 2.5.1 Simulation as `Miniature Theories'.