This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM. In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (ABM) is a powerful, simulation-modeling technique that has seen a dramatic increase in real-world applications in recent years. In ABM, a system is modeled as a collection of autonomous decision-making entities called “agents.” Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent—for example, producing, consuming, or selling. ABM is increasingly used for simulating real-world systems, such as natural resource use, transportation, public health, and conflict. Decision makers increasingly demand support that covers a multitude of indicators that can be effectively addressed using ABM. This is especially the case in situations where human behavior is identified as a critical element. As a result, ABM will only continue its rapid growth. This is the first volume in a series of books that aims to contribute to a cultural change in the community of empirical agent-based modelling. This series will bring together representational experiences and solutions in empirical agent-based modelling. Creating a platform to exchange such experiences allows comparison of solutions and facilitates learning in the empirical agent-based modelling community. Ultimately, the community requires such exchange and learning to test approaches and, thereby, to develop a robust set of techniques within the domain of empirical agent-based modelling. Based on robust and defendable methods, agent-based modelling will become a critical tool for research agencies, decision making and decision supporting agencies, and funding agencies. This series will contribute to more robust and defendable empirical agent-based modelling.

This book constitutes the refereed proceedings of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2015, held in Salamanca, Spain, in June 2015. The 10 revised full papers and 9 short papers were carefully reviewed and selected from 48 submissions are presented together with 17 demonstrations. The articles report on the application and validation of agent-based models, methods and technologies in a number of key application areas, including: agents and the energy grid, agents and the traffic grid, affective computing and agent development, ambient and contextual agents, social simulation and social networks and other agent-based applications.

This book provides practical guidance on research methods and designs that can be applied to Complex Dynamic Systems Theory (CDST) research. It discusses the contribution of CDST to the field of applied linguistics, examines what this perspective entails for research and introduces practical methods and templates, both qualitative and quantitative, for how applied linguistics researchers can design and conduct research using the CDST framework. Introduced in the book are methods ranging from those in widespread use in social complexity, to more familiar methods in use throughout applied linguistics. All are inherently suited to studying both dynamic change in context and interconnectedness. This accessible introduction to CDST research will equip readers with the knowledge to ensure compatibility between empirical research designs and the theoretical tenets of complexity. It will be of value to researchers working in the areas of applied linguistics, language pedagogy and educational linguistics and to scholars and professionals with an interest in second/foreign language acquisition and complexity theory.

The Routledge Handbook of Research Methods for Social-Ecological Systems provides a synthetic guide to the range of methods that can be employed in social-ecological systems (SES) research. The book is primarily targeted at graduate students, lecturers and researchers working on SES, and has been written in a style that is accessible to readers entering the field from a variety of different disciplinary backgrounds. Each chapter discusses the types of SES questions to which the particular methods are suited and the potential resources and skills required for their implementation, and provides practical examples of the application of the methods. In addition, the book contains a conceptual and practical introduction to SES research, a discussion of key gaps and frontiers in SES research methods, and a glossary of key terms in SES research. Contributions from 97 different authors, situated at SES research hubs in 16 countries around the world, including South Africa, Sweden, Germany and Australia, bring a wealth of expertise and experience to this book. The first book to provide a guide and introduction specifically focused on methods for studying SES, this book will be of great interest to students and scholars of sustainability science, environmental management, global environmental change studies and environmental governance. The book will also be of interest to upper-level undergraduates and professionals working at the science–policy interface in the environmental arena.

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 explores how integrated management of environmental resources via a Nexus Approach can help to achieve Sustainable Development Goals (SDGs). It takes a process-oriented view on what should or needs to be done to implement a Nexus Approach and how this relates to SDGs. After sketching the background and conceptual outline, contributions to the book explore key aspects of monitoring and implementation. Specifically, they: focus on the importance of monitoring resource use and how to advance it at the international level to support SDG implementation, exemplify the resources perspective on the nexus approach by exploring how to close the nitrogen cycle and stay within planetary boundaries, elaborate on proven and emerging strategies for nexus implementation, highlighting means to enhance, monitor and analyse stakeholder participation, explain how the horizontal and vertical nexus dimensions interact and can support SDG implementation. The book sheds new light on key aspects of the interrelation between SDGs and the Nexus Approach and provides specific recommendations how to advance it.

Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path to more efficient and sustainable lifestyles. The topics covered within include: households' attitudes toward recycling, designing decision trees for representing sustainable behaviors, negotiation-based parking allocation, auction-based traffic signal control, and others. This selection of papers will be of interest to social scientists who wish to learn more about agent-based modeling as well as experts in the field of agent-based modeling.