There are many social situations where people are assessed – as candidates in job recruitment, as potential partners on dating platforms, as potential beneficiaries in social service provision, as suspects in crime, as contenders in elections, etc. The practice of assessment and profiling is socially pervasive and constitutive: categorizing people according to their personal profiles for decision making is an essential component of the constitution of the social.  However, assessments are often subject to fairness issues, discriminatory practices and bias. Overcoming these requires investigation into the complex dynamics behind social assessment. This track seeks the submissions of papers introducing agent-based models that address assessment contexts and their dynamics. We aim to identify common insights, context-specific traits and policy consequences. Empirically grounded case studies are especially welcome.

“The management of healthcare systems requires interdisciplinary efforts and a complex perspective, relying on the intersection of different domains such as public health and social geography, among others. It is fundamental to the welfare of societies and characterized by a strong empirical application, with issues related to the availability and interoperability of data and privacy issues. This justifies a growing interest in agentbased modelling and integration with other methods to provide support to the management of health infrastructures and their usage by the population. The proposed special track aims to gather researchers with similar interests in this domain. We welcome contributions exploring recent developments, applications, and future venues on the subject. Topics of interest include (but are not limited to):

• Innovative hybrid methodologies for ABM and simulation methods”
• Accessibility to healthcare infrastructure and patients’ mobility
• Intersection with other topics (disaster management, disease diffusion…)
• Decision-making and management of healthcare infrastructures

Agent-based models capture complex social dynamics and are widely applied in economics, political science, and social science. However, their agents often rely on simplistic heuristic rules that, while adaptive, fail to reflect human cognitive capacity. This limitation constrains insights into how how complex human cognition and behavior impacts social systems. Advances in artificial intelligence, such as large language models and reinforcement learning, offer potential solutions. AI-enhanced agents could continuously learn adaptive strategies or employ language and other complex human traits. Although some initial applications exist, the option space for use cases remains largely unexplored. Additionally, the scientific potential of such models to enhance understanding of real-world systems remains unclear, as significant challenges may arise, such as computational complexity. This track invites contributions from economics, political science, and social sciences that employ AI at the agent level (and beyond) in agent-based models to advance the state of the art.

Visionary ideas, long-term challenges, new research opportunities, and controversial debate are at the core of this track. We encourage submissions of innovative, risky, and provocative ideas, which are clearly presented, rigorously developed, and critically reflected upon. Preliminary work or submissions reporting on existing approaches will not be accepted for this track. Accepted papers would reflect on: the use of social simulation and computational social science in solving contemporary challenges; new, forgotten, or underrepresented methodologies and application areas; their potential opportunities and risks; and on the future of the research area and its community within the broader social sciences and computing domains.

This special track explores cutting-edge advancements in social simulation and agent-based modelling within the context of climate change in cities. It focuses on the potential of mitigation and adaptation strategies toward climate-resilient and sustainable urban environments. The session will discuss innovative modelling methods and examine the impact of behavioural, social, technological, and institutional innovations across various domains, including urban forms, buildings, mobility and transport, and food systems. Key themes include but are not limited to, individuals’ behavioural and lifestyle changes, the emergence of social norms and societal transitions, social and technical tipping points, pathways to climate-resilient and decarbonized cities, governance and institutional frameworks, participatory modelling, and the role of AI and big data. Join us to explore how innovative solutions can drive urban transformations and address the complexities of climate action in cities.

The special track Complexity in Organization, Management, and Economics continues a series of successful sessions, emphasizing the growing role of agent-based modeling and simulation in organization, management, and economics. It explores how these methods enhance our understanding of complex dynamics in these fields. Key topics include organizational resilience, digital twins, discrimination, and subjective performance evaluation, as well as the role of agent-based models in sustainable economic transitions. From an economic perspective, the track examines market structures, decision-making in competitive environments, and the interplay between micro- and macroeconomic dynamics, including crises, business cycles, and climate change. A core social science focus lies in simulating human behavior, group decision-making, and collective intelligence. Additionally, the track addresses methodological advancements in empirical validation, hybrid modeling approaches, and strategies for ensuring transparency and reproducibility in agent-based research within organization, management, and economics.

A transition to a circular economy requires a tool to investigate its complex social interactions and dynamic linkages with product life cycles. Alongside resource extraction, manufacturing, transport, use, and end-of-life management of products, decision-making by consumers, producers, and other stakeholders and various policy options and uncertainty factors play roles, making social simulation using ABM a promising approach. However, diving into the complexity of circularity requires an interdisciplinary collaboration to model circularity and environmental impacts. The application of ABM in the circular economy is increasing, but further conceptual and methodological development and application are needed. For instance, it requires coupling with other methods like material flow analysis (MFA) and life cycle assessment (LCA), which are not yet fully integrated into the social simulation. In this session, we seek contributions about simulation studies on the socio-technical complexity of the circular economy and/or methodological development to couple multiple modelling techniques or stakeholder engagement. 

“This track focuses on submissions related to modeling of transformative change across social, economic, and environmental systems. Today’s rapidly changing world faces unprecedented challenges. Understanding transformative change (profound, systemic shifts that radically reshape underlying structures, processes, and relationships within a system) becomes increasingly critical. Work submitted to this track might include:

Applications of ABM to study adaptation, resilience, and transformation in complex socio-ecological systems
We particularly encourage submissions that address methodological challenges in modeling transformative change, integrate empirical data, or develop novel approaches to representing profound systemic shifts. Both theoretical contributions and applied case studies are welcome.”

• How systems respond to and generate radical shifts in behavior, policy, technology, economics, and environmental conditions
• The role of nonlinear interactions, feedback loops, and path-dependencies in driving or inhibiting transformative change
• Methods for modeling tipping points and cascading effects across different scales, from individual to institutional levels
• Approaches to capturing emergence and cross-scale dynamics in transformation processes

A prominent theme in social simulation is the behavioral and structural representation of institutions, be it in the form of conventions, social norms or formal institutions (e.g., legal rules). In this now fourth iteration of the special track, we invite for contributions that leverage an understanding of how build social structure from the bottom-up, drawing attention to the importance of normative processes and institutional features such as decision-making, governance arrangements, as well as explanatory accounts for the influence of the normative/institutional environment on societal outcomes. This track hence invites for conceptual or applied approaches focusing on 1- Theories and frameworks capturing norms and institutions in agent-based models 2- Methodologies for collecting data on norms and institutions (and related concepts) 3- Verification and validation of models of norms and institutions 4- Models incorporating institutional or normative concepts, including the study of dynamics 5- Models exploring the interaction between norms and “grown” or injected policies

Many academics consider qualitative evidence (e.g. texts gained from transcribing oral data or observations of people) and quantitative evidence to be incommensurable.  However, agent-based simulations are a possible vehicle for bridging this gap. Narrative textual evidence often gives clues as to the in-context behavior of individuals and is thus a natural source for behaviors to inform the specification of corresponding agent behavior within simulations. The texts will not give a complete picture, but will provide some of “menu” of behaviors people use. During this session we hope to further the understanding of how to improve this. We are particularly interested in accounts of the procedures or structures people used to bridge between qualitative and formal realms based in reported modelling experiences. Thus, those interested to present their work in this session have to make sure that their submission explicitly addresses the use of qualitative data in their modelling endeavour. The session is open to all approaches that seek to move from qualitative evidence towards a simulation in a systematic way. These include, but are not limited to:

• Approaches based in Grounded Theory.
• Tools for facilitating such a process.
• Participatory processes that result in a simulation.
• Frameworks for aiding the analysis of text into rules.
• Elicitation techniques that would aid the capture of information in an appropriate structure.
• Models and ideas from psychology to aid in the above process.
• Insights and tools from Natural Language Processing that may help this process.
• Agent architectures that will facilitate the programming of agents from such analyses.
• Philosophical or Sociological critiques, pointing out assumptions and dangers.
• Examples of where this approach has been tried. 

Replicating human-like decisions is at the core of domains such as agent-based modelling for social simulation, affective computing, or intelligent virtual agents. To advance in this area, we need theories, models, and methods for building agents / simulations that include authentic and realistic features of human deliberation (e.g., coherence with established psychological dynamics) while fitting within the constraints and purposes set by simulation (e.g., scalability).  The current prevalent approaches for modelling human decision-making mainly revolve on simplified decision processes, hence often entailing limitations for capturing the complex underlying psychological dynamics [1,2,3, 4] and hence the reliability of subsequent conclusions. If we want to improve both the range of phenomena we can cover and the realism of our agents / simulations, we need to strengthen the anchoring of our models in the decisional patterns identified by psychology, cognitive sciences, social sciences, and humanities. Moreover, operational methods for producing such models and enabling their integration within social simulations (e.g., added conceptual and computational complexity, adequate validation, explainability) remain to be established and are the subject of this track. This track is open to all approaches seeking to introduce human-like realism of deliberation / decision-making within agent design and/or social simulation, which include but are not limited to:

• theoretical papers introducing theoretical foundations from social sciences, cognitive sciences, humanities etc. and explaining how they can be integrated within agent design / social simulation;
• modelling papers proposing and testing the suitability of social sciences / cognitive sciences / humanities-inspired models in agent design / social simulations;
• methods & engineering papers introducing support for researchers and designers about various methods (e.g., games, Cognitive Task Analysis) that are relevant when deciding upon what data to collect and how, upon what and how to implement and use human-like agent deliberation processes in modelling practices;
• survey papers reviewing models formerly produced in fields such as social simulation, affective computing, games design, or intelligent virtual agents, and identifying their strengths and weaknesses and pathways for improvement; as well as overviews of psychology, philosophy, and sociology research describing relevant theories, world-views, approaches, and phenomena relevant for model production;
• critique papers scrutinizing the designs and implementations of human deliberation / decision-making from perspectives such as critical theory, ethics, and impact;
• vision papers identifying areas in society and/or psychology where social simulation could achieve high impact should a specific feature of human deliberation / decision-making is available. ESSA SIG-MOOD — Models of Human Decision

This special track focuses on modelling and simulation of fishery systems and is a response to the current European push towards managing complex socio-techno-ecological systems through infrastructures such as the EU Digital Twin of the Ocean. The session is interested in bringing together researchers and practitioners working on representing socio-ecological aspects of fishing, with special attention to providing tools for sustainable management of fishery activities. The session aims to cast a wide net, with examples of interest including but not limited to:

• Digital Twin of the Ocean
• Models focusing on fishing fleet activities, biology or economics,
• Learning and adaptation in fishing fleet/fish behaviour,
• Complex, multi-level models integrating relevant aspects of fisheries,
• Work on model coupling,
• Empirical calibration, sensitivity analyses and approaches to quantifying uncertainty,
• Examples of participatory modelling of fisheries,
• Work on using secondary data to inform fisheries models,
• Work on assuring interoperability of topic-relevant data from multiples sources,
• Examples of the use of the European Union
• Digital Twin of the Ocean

The Social Identity Approach (SIA) is a promising approach from the social sciences that describes how people behave while being part of a group, how groups interact and how these interactions and ‘appropriate group behaviours’ can change over time. We regard the combination of SIA & ABM as a promising combination that enables us to push the frontiers in understanding human (group) behaviour in its social environment. We also know that formalizing a complex theory is challenging, and would like to offer an environment where formalizations can be shared and discussed.
In this special track of the ESSA special interest group SIAM, we invite any submissions that focus on formalising aspects of social identity with agent-based modelling. This might also be on relevant theoretical concepts such as norms or social influence. We welcome a variety of application domains and invite for reflection on the way formalisation choices have been made.

This session presents ABMs that involve dynamic processes over networks. This includes diffusion of ideas and behaviour (eg opinion polarisation, adoption of innovations) or of something more tangible (eg disease, trade goods). It also includes the way in which networks shape macro-level outcomes (eg social inequality, conflict, collaboration). We also welcome contributions that concern the dynamics of networks themselves (eg SAOM, network generators).

“This special track focuses on the interplay between social simulation and games. We wish to bring together researchers working in both fields at a crossroads where synergies will be created between the two areas. (NB! The games domain is not the same with the game theory one.)

• Game design. What level of abstraction is chosen for a game intended to be combined with an agent-based model (ABM) in a research setup? What game elements / game mechanics are useful?Modelling the social situation. Which approach captures the situation with sufficient granularity? How should a choice be made to include specific theories and models that describe the situation?
• Example implementations. Stories of success and failure: Which elements in a game that includes social interaction turn out to be useful, and which are counter-productive? Which elements of social simulations can be used in the design of games? How can you document the games & ABM research design in a useful way?

This track focusses on discussion regarding challenges in model development, verification, and validation as well as other methodological challenges. Social simulation as a method, the other side of the coin, puts the use of social simulation as an alternative to other methods of enquiry central. In both broad categories, the trans/inter/multidisciplinary collaboration stumbling blocks may benefit from a more general discussion as well, to avoid getting tied up in case-specificities. Finally, transparency and reproducibility demands are of interest.

The technical aspects of social simulation track invites papers on the platforms, frameworks, and programming language used (or could be used) for social simulation, and their characteristics such as scalability, usability (form a researcher, modeler, and end-user perspective), execution speed, etc. This includes the use of high-performance computing, cloud computing, and exascale computing but also the use of generative AI in the development and implementation of social simulation models, interface issues etc.

This 3-hour tutorial will provide a hands-on introduction to Repast4Py, an agent-based modeling framework written in Python that provides the ability to build large, distributed agent-based models (ABMs) that span multiple processing cores. Distributed ABMs on high-performance computing (HPC) resources enable capturing of unprecedented details in large-scale complex systems. However, the specialized knowledge required for developing such ABMs creates barriers to wider adoption. Repast4Py is designed to provide an easier on-ramp for researchers from diverse scientific communities to apply large-scale, distributed ABM methods. The tutorial will be divided into three sections: 1) An introduction to and motivation for distributed ABM with a presentation of Repast4Py’s distributed ABM components; 2) hands-on coding exercises building Repast4Py models; and 3) discussions of performance related coding techniques. In addition to running the model locally, we will also execute it at much larger scales (100s of process ranks), running on Argonne National Laboratory’s Bebop cluster.  

There has been a long standing workshop and track on Qual2Quant where people discuss the use of qualitative data for Social Simulations. In this workshop we want to build on this and look specifically how ethnographic methods can be used to develop social simulations. As ethnographic methods emphasize the description of phenomena from the perspective of the humans that are involved, they provide many handles for modeling agents, processes, mechanisms and rules, as well as environmental contextual information that can be extremely relevant for the simulations of these phenomena. Through our work over the last few years, we have gained experience with modeling a simulation to support the management of mining disasters. But also on how teams adapt to disruptive innovation technology when they manage leakages on an extensive pipe networks carrying warm water for heating. And another on how people make decisions on energy consumption, which will be used to simulate the energy consumption of a new sustainable neighborhood. Very different applications but similar methods were used. In the workshop we plan to concretely explore how this type of ethnographic data can be used in a more systematic way to create social simulations. 

In this 3-hour workshop, we want to discuss some of the core questions when designing an agent-based model: a) how to select a decision model or theory to base the conceptual model on, and b), how to formalize the decision model or theory chosen into programming code. Both steps are challenging and don’t follow a standard routine. Expertise from psychology, such as how to perform a behavioural analysis to systematically examine a specific behaviour (understanding why it occurs and identifying the key factors that influence it) can be of help. We have developed and discussed several approaches which we will share and put to a hands-on discussion on theory selection and the formalization process. We hope that in this workshop we can jointly identify guiding principles and best-practice examples by learning from each-others work.

Reusable model components can be a key to accelerating theory development and agent-based model implementation. By providing atomic process implementations, they enable researchers to understand, compare and reuse model components without having to understand an entire model and its context. This speeds up new modelling projects, fosters synergies, and improves code correctness as components are tested many times. In this workshop we will introduce and discuss the concept of reusable building blocks as proposed by Berger et al. (2024). In a hands-on session, participants will develop concepts for their own building blocks following the template of the agentblocks.org repository. We will navigate common challenges in designing and implementing reusable components, and discuss open challenges to drive community collaboration. This workshop is for agent-based modellers eager to share, refine, and discuss their model components – helping to shape a collective effort towards social simulation models that are reusable, transparent and state-of-the-art.