Day 1 – Wednesday, 15 March

09:30 - 11:00


By Tatiana Filatova (Delft University of Technology, The Netherlands)

Computing societal dynamics in response to climate change

Climate is changing and will cause substantial disruption to socio-economic systems worldwide. While a possibility of crossing thresholds and triggering abrupt irreversible changes in socio-environmental systems is foreseen, the development of models to study their emergence and effects is challenging due to inherit uncertainties in computing societal dynamics. Agent-based models (ABMs) offer a prominent way to represent human behavior in coupled models of socio-environmental systems. This method allows for a detailed representation of various behavioral strategies of agents grounded in different theories and data, explicit modeling of their learning and adaptation behavior and of social interactions. In the past years empirical ABMs proliferate, fueled by the emergence of new data collection methods, especially on the social dynamics side. In this talk I will discuss the challenges of combining theory and data to model individual adaptive behavior and illustrate it with an example of individual behavioral change and evolving market institutions in response to flood hazards. I focus on the issue of data that can be instrumental in defining rules for agents’ choices, behavioral change, learning and interactions in the climate change context where past data may not represent future trends and where regime shifts are expected.
I will also finish with discussing the upcoming open access community platform for sharing reusable building blocks of an ABM code. Such building blocks could represent diverse theories of human behavior, their alternative implementations based on the context, rules guiding agents’ interactions and learning and etc. I look forward to an exciting discussion!

11:00 – 11:15



11:15 - 12:45

Social Identity Approach Modelling: formalising mechanisms

By  Geeske Scholz (Delft University of Technology, the Netherlands) and
Nanda Wijermans (Stockholm University, Sweden)

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. Many challenges we face have individuals that feel as part of a group at the heart of the problem and solution. Examples are overcoming resource overexploitation with collective action, social movements, engaging in protest, or online polarisation etc.. Understanding such developments or problems requires an understanding of the social (within and between) group dynamics. Enriching social simulation models with SIA can address the need to integrate social context and its influence on agents’ behaviours. However, formalising SIA mechanisms in an ABM is far from trivial, as it entails translating verbal (and at times ambiguous) theory into formulas or if-then rules. In our opinion, this challenge is best understood and addressed in direct experience and group work. We want to use this session to jointly engage in the challenge to formalise two crucial SIA mechanisms: a) how and how much a salient (“activated”) social identity influences behaviour; and b) how an agent can identify and select groups (linked to normative contrast and the meta-contrast ratio). This workshop is organised as an activity of the SIG-SIAM (social identity approach modelling) of the European Social Simulation Association (ESSA), so this is also an opportunity to join the SIG-SIAM network.


  • 5 min intro 
  • two short (2 x 10 minutes) presentations of ABMs including the social identity approach and a specific formalisation challenge (i.e., formalising one of the two mechanisms);
  • breakout group discussions in which we jointly work on formalising mechanisms (30 mins); and
  • reporting back and summarising outputs as well as challenges we came across (30 mins).

12:45 – 13:30

Lunch break


13.30 - 15:00

How to do wrong using Social Simulation -as a result of arrogance, laziness or ill intent.

By Bruce Edmonds, (Manchester Metropolitan University, UK)

It is often assumed that those doing social simulation are positively motivated, and, for the overwhelming part, that is true. In order to stimulate discussion and generate new perspectives, this session will reverse the normal perspective and look at how social simulation could result in harm to people’s lives as a result of either arrogance, laziness or ill intent. Hopefully the result of the session will be the identification of ways in which social simulation modelling might be the opposite of helpful and how to notice that these are occurring. Participants will be encouraged to describe a sequence of events in which a social simulation plays an essential role where the outcomes are negative overall, along with the motivations behind this and the kind of impact it might have. A future, follow-up session (online or SimSoc2023) will look at how such modelling might be prevented, caught or mitigated. ....

15:00 – 15:15



15:15 - 16:45

Synthetic populations 

By Gary Polhill (James Hutton Institute, UK) and Mario Paolucci (Institute of Cognitive Sciences and Technologies at CNR, Italy)

Empirical agent-based modelling often requires the creation of synthetic populations of agents from survey, census and other data. Ideally these would have similar statistical properties to the empirical population, including joint distributions of various attributes including: demographics, psychological variables, spatial location, social networks, daily routines, and decision-making options. While there is a large literature on population synthesis, reviewed recently in JASSS by Chapius et al. (, these methods focus mostly on the generation of realistic attributes for the agents. Though of course this is important, with agent-based models we need to know that agents with assigned attributes are leading appropriate artificial lives with appropriate other agents. This offers some explanation for why Chapius et al. do not find ‘off-the-shelf’ methods being used by the empirical agent-based modelling community to initialize their populations.


In this workshop, we want to bring together a community-of-practice in population synthesis for empirical agent-based modelling, with a view to organizing follow-on activities.



10 mins: Welcome, summary of the aims of the workshop and agenda

20 mins: Four short (five-minute, two slides max. plus title slide) invited presentations by people who have created synthetic populations in ABMs, summarizing methods, data and gaps.

10 mins: Q&A session

20 mins: Breakout groups – discuss personal experiences and collate on virtual whiteboards – needs/requirements; gaps/challenges; key references

10 mins: Report back from breakouts

20 mins: Next steps – using on-line voting, etc. to assess options