This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration - one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.

Methodological Guidelines for Modeling and Developing MAS-Based Simulations The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field's history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications. Simulation for MAS - explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction. MAS for Simulation - discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools - presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue. Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.

Inspired by the interesting contributions to the 6th Conference on Compu- tional Methods in Systems Biology (CMSB 2008) and the Dagstuhl Seminar 09091on"FormalMethods inMolecular Biology"inFebruary2009, papershave been selected for this special issue of the journal TransactionsonComputational Systems Biology, under the title Modeling Methodologies. The special issue starts with a position paper on "Biomodel Engineering - from Structure to Behavior," which discusses the potential that concepts from traditional computing science hold for creating more powerful models of biol- ical systems and identi?es venues for challenging future research. The technical contributions of the special issue covera broadrangeof mod- ing methodologies that have recently been developed in computational systems biology. First, twonewmodelinglanguagesarepresented.The"Attributed?-Calculus withPriorities"presentsacombinationofaconcurrentprocesslanguage, i.e., the ?-calculus, and a sequential core language, i.e., the ?-calculus; being equipped withprioritiesthelanguageenablesthedescriptionofdiversespatialphenomena, di?erent kinetics, as well as an individual-based and population-based modeling of biological systems. It is shown how the di?erent dialects of the ? calculus, including the pi@-calculus, can be expressed. Its stochastic semantic is ?rmly rooted in CMTC's and is re?ected in the stochastic simulator.

This volume contains the proceedings of the 6th Conference on Computational Methods in Systems Biology (CMSB) held in October 2008 in Rostock/ Warnemunde. ] The CMSB conference series was established in 2003 to promote the c- vergence of (1) modelers, physicists, mathematicians, and theoretical computer scientists from ?elds such as language design, concurrency theory, software ve- ?cation, and (2) molecular biologists, physicians, neuroscientists joined by their interest in a systems-level understanding of cellular physiology and pathology. Sincethistime, theconferencehastakenplaceannually. Theconferencehasbeen held in Italy, France, and the UK, and we were glad to host CMSB in Germany for the ?rst time. The summaries of the invited talks by Hidde de Jong, Jane Hillston, Koichi Takahashi, Nicolas Le Novere, and Dieter Oesterhelt are included at the - ginning of the proceedings. The 21 regular papers cover theoretical or applied contributions that are motivated by a biological question focusing on modeling approaches, including process algebra, simulation approaches, analysis methods, in particular model checking and ?ux analysis, and case studies. They were - lected out of more than 60 submissions by a careful reviewing process. Each paper received at least three reviews from members of the Program Committee consistingof27renownedscientistsfromsevencountries. We wouldliketothank all members of the Program Committee and the referees for the thorough and insightful reviews and the constructive discussions. Due to the number of hi- quality submissions, the decision on which papers to accept or reject was not easy. Therefore, we integrated a rebuttal phase for the ?rst tim

This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration - one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.