Aimed at readers with minimal experience in computer programming, this brief book provides a theoretical and methodological rationale for using ABM in the social sciences. It goes on to describe some carefully chosen examples from different disciplines, illustrating different approaches to ABM. It concludes with practical advice about how to design and create ABM, a discussion of validation procedures, and some guidelines about publishing articles based on ABM.
This clear and coherent book introduces agent-based modelling (ABM) to those who are not familiar with nor have been previously exposed to computational simulation. Featuring examples, cases and models, the book illustrates how ABM can, and should, be considered as a useful approach and technique for the study of management and organisational systems. Davide Secchi begins by explaining what ABM has to offer as opposed to other techniques, emphasising its suitability to the study of complex social systems. While dissecting the core components of the approach, he introduces key elements and mechanisms with a practice oriented approach rather than insisting solely on logic and theory. With an emphasis on applications and using examples from NetLogo -- one of the most widely used agent-based software platforms -- the book guides the reader through a step-by-step process on how to develop a computational simulation. Featuring a hands-on applied approach that makes a difficult topic easy for non-modellers, How Do I Develop an Agent-Based Model? will be a key resource for business and management Masters-level students embarking on a dissertation project. It will also be a useful reference for PhD students in the field, as well as a starting point for academics who would like to begin using ABM in their research.
As Michael finally finds the person who left him for dead, can the love he'd found with Alex survive the fallout? Michael survived a hate crime but is haunted by memories beyond his grasp and plagued by relentless nightmares. When he leaves his life as a catwalk model ad returns home to confront his past, it’s his present in the shape his persistent agent, Alex, who refuses to leave him alone. Once he thought he loved Alex, but their relationship crumbled is destroyed when Alex's well-intentioned but suffocating tendency to protect Michael becomes their downfall. Michael loves Alex, and always will, and protecting the man he loves is everything. Only, in protecting Michael he loses everything, and he wants a second chance to prove that he can change. When he’s drawn into the darkness of Michael’s past, he’s determined to be a very different kind of person—someone Michael can depend on. Secrets rarely remain hidden, and the pursuit of the person who nearly took Michael's life presents a formidable challenge. The prospect of remaining passive becomes increasingly difficult as danger looms closer. Will history repeat itself, causing Alex to lose Michael once more?
The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.
This book assesses the use and limitations of the principal-agent model in a context of increasingly complex political systems such as the European Union. Whilst a number of conceptual, theoretical and methodological challenges need to be addressed, the authors show that the principal-agent model can still provide deeper insights into a wide range of political phenomena. Through an empirical analysis of multiple principal-agent relations in the EU, covering a variety of policy fields and political actors, the volume refines our theoretical understanding of the politics of delegation and discretion in the EU. It will appeal to scholars in interested in EU politics and policy, public administration and governance, and international organisations. The chapter ‘Multiple principals preferences, different types of oversight mechanisms, and agent’s discretion in trade negotiations’ is published open access under a CC BY 4.0 license via link.springer.com.
The essential textbook on agent-based modeling—now fully updated and expanded Agent-Based and Individual-Based Modeling has become the standard textbook on the subject for classroom use and self-instruction. Drawing on the latest version of NetLogo and fully updated with new examples, exercises, and an enhanced text for easier comprehension, this is the essential resource for anyone seeking to understand how the dynamics of biological, social, and other complex systems arise from the characteristics of the agents that make up these systems. Steven Railsback and Volker Grimm lead students stepwise through the processes of designing, programming, documenting, and doing scientific research with agent-based models, focusing on the adaptive behaviors that make these models necessary. They cover the fundamentals of modeling and model analysis, introduce key modeling concepts, and demonstrate how to implement them using NetLogo. They also address pattern-oriented modeling, an invaluable strategy for modeling real-world problems and developing theory. This accessible and authoritative book focuses on modeling as a tool for understanding real complex systems. It explains how to pose a specific question, use observations from actual systems to design models, write and test software, and more. A hands-on introduction that guides students from conceptual design to computer implementation to analysis Filled with new examples and exercises and compatible with the latest version of NetLogo Ideal for students and researchers across the natural and social sciences Written by two leading practitioners Supported by extensive instructional materials at www.railsback-grimm-abm-book.com
Multi-agent systems have been a focus of studies for more than 25 years. Yet, despite substantial effort of an active research community, modeling of multi-agent systems still lacks complete and proper definition, general acceptance, and practical application. This book provides the Agent-Modeling Language (AML), a comprehensive modeling language as an extension of UML 2.0, concentrating on multi-agent systems and applications.
A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
From the Foreword: "This book exemplifies one of the most successful approaches to modeling and simulating [the] new generation of complex systems. FLAME was designed to make the building of large scale complex systems models straightforward and the simulation code that it generates is highly efficient and can be run on any modern technology. FLAME was the first such platform that ran efficiently on high performance parallel computers and a version for GPU technology is also available. At its heart, and the reason why it is so efficient and robust, is the use of a powerful computational model ‘Communicating X-machines’ which is general enough to cope with most types of modelling problems. As well as being increasingly important in academic research, FLAME is now being applied in industry in many different application areas. This book describes the basics of FLAME and is illustrated with numerous examples." —Professor Mike Holcombe, University of Sheffield, UK Agent-based models have shown applications in various fields such as biology, economics, and social science. Over the years, multiple agent-based modeling frameworks have been produced, allowing experts with non-computing background to easily write and simulate their models. However, most of these models are limited by the capability of the framework, the time it takes for a simulation to finish, or how to handle the massive amounts of data produced. FLAME (Flexible Large-scale Agent-based Modeling Environment) was produced and developed through the years to address these issues. This book contains a comprehensive summary of the field, covers the basics of FLAME, and shows how concepts of X-machines, can be stretched across multiple fields to produce agent models. It has been written with several audiences in mind. First, it is organized as a collection of models, with detailed descriptions of how models can be designed, especially for beginners. A number of theoretical aspects of software engineering and how they relate to agent-based models are discussed for students interested in software engineering and parallel computing. Finally, it is intended as a guide to developers from biology, economics, and social science, who want to explore how to write agent-based models for their research area. By working through the model examples provided, anyone should be able to design and build agent-based models and deploy them. With FLAME, they can easily increase the agent number and run models on parallel computers, in order to save on simulation complexity and waiting time for results. Because the field is so large and active, the book does not aim to cover all aspects of agent-based modeling and its research challenges. The models are presented to show researchers how they can build complex agent functions for their models. The book demonstrates the advantage of using agent-based models in simulation experiments, providing a case to move away from differential equations and build more reliable, close to real, models. The Open Access version of this book, available at https://doi.org/10.1201/9781315370729, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
"The Art of Agent-Oriented Modeling is an introduction to agent-oriented software development for students and for software developers who are interested in learning about new software engineering techniques."--Foreword.
