This book covers the latest advances in applying agent-based modelling in social sciences. The Social Simulation Conference is the major global conference devoted to this topic. It is aimed at promoting social simulation and computational social science.

This year’s special theme is “Social Simulation—Crossroads Between Social Science and Computational Methods”, focused on modelling of social phenomena, computational aspects and the theory linking these two scientific fields.

The primary audience of this book are scholars and practitioners in computational social sciences including economics, business, sociology, politics, psychology and urban studies.

Demonstrations that include virtual reality (VR) technologies are becoming increasingly common in research contexts. All included roles within a demonstration experience (facilitators, participants, and spectators) take up different responsibilities to be able to run through a VR demonstration as intended. VR head-mounted displays (HMDs) are particularly difficult to demonstrate with considering the participant’s restricted vision of their surroundings and the facilitator. There is limited HCI research that has analyzed interactions between the roles of a demonstrations when using VR HMDs. Therefore, this study explores how these roles address the challenges that arise during VR demonstrations. With a video-analytic approach, we gathered data from live demonstrations from an ACM conference in 2024. To articulate the data gathered, we encompass the concepts of breakdown and repair, alignment and common ground, and progressivity. Our findings highlight five forms of alignment work: procedural, technological, conversational, visual, and physical alignment, as well as preemptive repurposed conversational repair strategies. This paper’s main contribution is the forms of alignment that provide discourse tools for analyzing alignment work interactions and understanding them in the context of VR demonstrations. Additionally, this research provides actionable guidelines aiding VR-experience organizers as a way to limit breakdowns and arrested progressivity in their demonstrations, applicable in context from lab-based experiments to public exhibitions. These guidelines include to inform sequentiality, inform about differences in interactions and technologies, preempt physical surroundings, and negotiate touch. We conclude by encouraging future research to explore implications of designing for interactions and designing for specific demonstration roles.

This paper builds on the contribution of Anzola, Barbrook-Johnson and Gilbert (J Artif Soc Social Simul 25(4):1, 2022) with a view to furthering the community’s discussion of ethical principles associated with our endeavours. We give particular attention to empirical applications of agent-based social simulation.

Generative AI is all over the place, mainly in the form of large language models (LLMs). Recently, LLM researchers moved into the world of replacing human participants in social and behavioural science research and even social simulation. In this paper we want to make our community aware of these developments, discuss our worries but also the potential for using LLMs productively with agent-based social simulation, and pose some questions to the LLM approach to social simulation.

During the Social Simulation Conference 2023 in Glasgow a discussion in one of the general sessions brought the idea to have an informal description of the past, present, and future of agent-based social simulation. Who better to offer such a paper than the collection of ESSA presidents so far? It forms the core of the ESSA organizational memory is you wish, and given the variety in backgrounds, experiences, and interests among them, there is something for everyone, reflecting the multitude of positions in the ESSA and SSC community.

This book contains the proceedings of the 18th Social Simulation Conference (SSC) and covers the state of the art of social simulation modeling. The SSC is the annual conference of the European Social Simulation Association (ESSA) and the major global conference devoted to this topic. It is aimed at promoting social simulation and computational social science. The book is the biggest collection of agent-based modeling research. It covers all aspects of modeling, from theory and philosophy of modeling to question of model design, purpose, and structure, using data, visualization, model interrelation, and open modeling.

This book is targeted at researchers in social simulation regardless of disciplinary backgrounds, across career stages and different sectors, such as academia, industry, and policy

Agent-based models have continuously increased regarding the implementation of the complexity of agent decision making. This poses questions for the ontological foundation of ABM as well as having implications for research design and data collections. This paper situates the meta-modelling framework CAFCA within other contextual and multidimensional agent-architectures, in particular focusing on its contributions to ontology and research design. We also present the challenges for data collection as a consequence of this increased representational complexity.

This chapter provides an overview of and introduction to the proceedings of the Social Simulation Conference 2023. It contains a short intro to social simulation, to the theme of social simulation and public health and the papers accepted from the conference. As a maturing methodology, social simulation has made inroads into substantive disciplines. The conference had a particular focus on applications of social simulation in public health. Over the past decade public health research has embraced social simulation as a method to better understand the population effects of interventions, to model interactions between individual and socio-economic effects on health and to understand the role of social influence in health behaviours. This chapter gives a brief overview of social simulation, its application in public health and provides an overview of the proceedings papers. 

This paper introduces the design intent “meaningful distrust” by analyzing existing gameplay design patterns and complementary theories from the social sciences. To explore meaningful distrust as a design intent, we have analyzed 4 very different games to see what relations and combinations of gameplay design patterns naturally occur, with mappings to relevant theories from the social sciences. This analysis focuses on how the design patterns are combined and how this affects the overall social situation in these games, adding to our understanding of how to design for meaningful distrust.

Agent-based models of human behaviors in emergencies are extremely important in prevention, preparedness, response, and mitigation of crises. However, there is huge variation in the modeling of human cognitions and actions, with varying degrees of realism and even more diverse definitions of how realism should be implemented in the models. The aim of this Rapid Literature Review is to identify existing patterns in modelling realistic behaviours in simulation models of disasters and crises, but also to identify gaps in the literature on the basis of a qualitative assessment of review papers on the topic. We analyze eight papers (identified through a search of 68 papers in the Scopus database) that review ABM models designed either to investigate general behaviors in emergencies (i.e., evacuations), or reactions to specific crises (i.e., COVID-19). Our analysis shows that while all the papers agree in advocating for more realism in modeling human behavior, very little has been done in terms of designing agents, interactions and environments that can be considered realistic.