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"Agent-Based Computational Modeling and International Relations Theory: Quo Vadis?" published on by Oxford University Press.

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.

The environmental impacts caused by construction waste have attracted increasing attention in recent years. The effective management of construction waste is essential in order to reduce negative environmental influences. Construction waste management (CWM) can be viewed as a complex adaptive system, as it involves not only various factors (e.g., social, economic, and environmental), but also different stakeholders (such as developers, contractors, designers, and governmental departments) simultaneously. System dynamics (SD) and agent-based modeling (ABM) are the two most popular approaches to deal with the complexity in CWM systems. However, the two approaches have their own advantages and drawbacks. The aim of this research is to conduct a comprehensive review and develop a novel model for combining the advantages of both SD and ABM. The research findings revealed that two options can be considered when combining SD with ABM ; the two options are discussed.

"Agent-Based Modeling in Political Decision Making" published on by Oxford University Press.

Virtually all current major social and environmental challenges such as financial crises, migration, the erosion of democratic institutions, and the loss of biodiversity involve complex systems comprising decision-making, interacting, adaptive agents. To understand how such agent-based complex systems function and respond to change and disturbances, agent-based modeling (ABM) is increasingly recognized as the main way forward. Many motivating examples of agent-based models exist that are realistic enough to successfully support the management of complex systems, but these solutions are case-specific and contribute few general insights into the functioning of systems. General theory, though, is highly needed because we cannot model each system and question. Still, across disciplines, a critical mass of expertise has accumulated that could transform ABM into a more coherent and efficient approach to discover the functioning of complex social-economic-ecological systems. To this end, we need a cross-disciplinary discussion among researchers and a goal-oriented synthesis to identify the general principles and theories essential to improve our understanding and management of complex systems.

Cover -- Abstract -- Contents -- 1 Introduction -- 1.1 Agent-Based Modeling: A Brief Historical Review -- 1.2 Agent Network Dynamics -- 1.3 Outline of the Book -- 2 Network Awareness in Agent-based Models -- 2.1 Network Awareness -- 2.2 First-Generation Models: Lattices -- 2.3 Second-Generation Models: Graphs -- 2.4 Additional Notes -- 3 Collective Dynamics of Adaptive Agents -- 3.1 Collectives -- 3.2 Binary Choices with Externalities -- 3.3 Adaptive Choices with Reinforcement -- 3.4 Network Effects on Adaptive Choices -- 4 Agent-Based Models of Social Networks -- 4.1 Introduction

Mathematical models and computer simulations play a crucial role in the context of the COVID-19 crisis for knowledge about the possible course of the pandemic and for appropriate policy decisions. The paper presents results from an ethnographic study of a government-funded R & D project dealing with agent-based modeling and simulation (ABMS) in the context of pandemic management. Based on the assumption that the use of computer simulations in pandemic management is not only a means to an end for political or epidemiological goals but also plays a significant role in determining which goals and strategies appear politically legitimate, the paper reconstructs how insights into the pandemic are generated in ABMS and specifically in the researched project and made accessible for decision-making.

The significant progress observed in the field of artificial economy opens up new possibilities for modeling economic growth. Agent-based models (ABM) allow leaving the concept of a representative agent in the past and linking investment decisions of economic agents at the micro level with long-term macroeconomic growth. Modern ABMs offer new algorithms for modeling expectations, agent interaction, technical progress, pricing, and production planning. Our article analyzes the current state of modeling investment in fixed assets in operating macroeconomic ABMs. The subject of the review is the families of models Eurace, CATS, KS, Jamel, Lagom. The authors also present the investment block of the agent-based multiregional input-output model (ABMIOM) being developed. Comparative analysis demonstrates that modern ABMs, as a rule, implement the principle of stock-flow consistency. Modeling the investment process requires detailing the commodity nomenclature, so that the initially adopted two-sector division into investment and consumer goods is replaced by more detailed structures, which gives rise to the problem of accounting for inter-sectoral relations in production and consumption. The Leontief production function copes with this problem, which is confirmed by its widespread use in ABM. The size of firms' investments is often derived from the need to expand capacity in accordance with the current production plan, so that planning turns out to be myopic, and long-term aspects in ABM are still largely unrealized. Nevertheless, already now ABMs reproduce many phenomena associated with the economic cycle. The developed ABMIOM provides horizontal consistency of cash flows between agents and analysis of results using input-output tables. ABMIOM represents a step forward in reflecting intersectoral and interregional flows. The model reproduces the growth and contraction of the economy as a result of independent investment decisions of individual firms and households, which is reflected in the sectoral and spatial structure of the economy. Further development of ABMIOM is associated with the modeling of savings, intrafirm finance, money market, innovation and technical progress.