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 two-volume set LNCS 12777 and 12778 constitutes the thoroughly refereed proceedings of the 12th International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, DHM 2021, which was held virtually as part of the 23rd HCI International Conference, HCII 2021, in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. DHM 2021 includes a total of 56 papers; they were organized in topical sections named: Part I, Human Body, Motion and Behavior: Ergonomics, human factors and occupational health; human body and motion modeling; and language, communication and behavior modeling. Part II, AI, Product and Service: Rethinking healthcare; artificial intelligence applications and ethical issues; and digital human modeling in product and service design.
This collection of excellent papers cultivates a new perspective on agent-based social system sciences, gaming simulation, and their hybridization. Most of the papers included here were presented in the special session titled Agent-Based Modeling Meets Gaming Simulation at ISAGA2003, the 34th annual conference of the International Simulation and Gaming Association (ISAGA) at Kazusa Akademia Park in Kisarazu, Chiba, Japan, August 25–29, 2003. This post-proceedings was supported by the twenty-?rst century COE (Centers of Excellence) program Creation of Agent-Based Social Systems Sciences (ABSSS), established at the Tokyo Institute of Technology in 2004. The present volume comprises papers submitted to the special session of ISAGA2003 and provides a good example of the diverse scope and standard of research achieved in simulation and gaming today. The theme of the special session at ISAGA2003 was Agent-Based Modeling Meets Gaming Simulation. Nowadays, agent-based simulation is becoming very popular for modeling and solving complex social phenomena. It is also used to arrive at practical solutions to social problems. At the same time, however, the validity of simulation does not exist in the magni?cence of the model. R. Axelrod stresses the simplicity of the agent-based simulation model through the “Keep it simple, stupid” (KISS) principle: As an ideal, simple modeling is essential.
Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: • Definition – The reader will learn how to plan a project and communicate using a charter. • Input analysis – The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. • Simulation – The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. • Output analysis – The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. • Decision support – Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.
The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. Examples include population dynamics, evolution of social norms, communication structures, patterns in eco-systems and socio-biology, natural resource management, spread of diseases and development processes. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases.
This special issue of the Journal of Economics and Statistics is devoted to the use of agent-based models for economic policy advice. It presents a collection of research papers in different fields of applications. Special emphasis is laid on discussing the potential and possible limitations of agent-based models for economic policy advice. The editorial provides an overview on the role of agent-based modeling in economic policy referring also to the papers presented. Furthermore, it highlights the strength of the approach, i.e., the explicit microfoundation and the modeling of heterogenous agents. Finally, we also report on current limitations of the method with regard to economic policy advice and point at some areas deserving further research.
Agent-based simulation has become increasingly popular as a modeling approach in the social sciences because it enables researchers to build models where individual entities and their interactions are directly represented. The Second Edition of Nigel Gilbert's Agent-Based Models introduces this technique; considers a range of methodological and theoretical issues; shows how to design an agent-based model, with a simple example; offers some practical advice about developing, verifying and validating agent-based models; and finally discusses how to plan an agent-based modelling project, publish the results and apply agent-based modeling to formulate and evaluate social and economic policies. An accompanying simulation using NetLogo and commentary on the program can be downloaded on the book's website: https://study.sagepub.com/researchmethods/qass/gilbert-agent-based-models-2e.
Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.
