Dear colleagues,
If you are working with making more realistic models of human deliberation, please consider submitting your work (long paper, short paper, extended abstract, poster) to the special track “Sense & Sensibility: Modelling human deliberation and decision-making” at the Social Simulation Conference (September 2023, Glasgow, The UK).
This special track is supported by the ESSA SIG MOOD (Models of Human Decision).
Looking forward to receiving your contributions,
Loïs, Melania, Friederike, and Vivek.
Special track @ SSC2023: Sense & Sensibility: Modelling human deliberation and decision-making
Track chairs:
Loïs Vanhée, Umeå University, Sweden
Melania Borit, UiT the Arctic University of Norway, Norway
Friederike Wall, University of Klagenfurt, Austria
Vivek Nallur, University College Dublin, Ireland
Replicating human-like decisions is at the core of agent-based social simulation. As such, we need data, theories, models, and methods for the design and validation of agents that reproduce authentic and realistic features of human deliberation (e.g. most deprived needs tend to yield to the greater corrective action) while also accounting for the constraints and aims of social simulations (e.g. covering specific social phenomena, scalability to many agents).
The current prevailing approach to model human decision-making in social simulation revolves around the random selection of behaviors from data-driven probability distributions. While this approach has its benefits, it can be blind to psychological dynamics that may be key to the accuracy of the conclusions of the model (e.g. coherence of decisions over time) [1,2,3]. If we want to expand the range of phenomena social simulation can cover and the quality of our simulations and conclusions derived from them, we need our models to be further anchored in the findings identified by psychology and cognitive sciences. However, the questions of how to produce such models and how to balance the specific considerations they entail (e.g. time, collaborative effort, complexity, validation, social implications) with simulation benefits (e.g. realism, explainability) remain open and are the subject of this special track.
This track is open to all contributions dedicated to the study of agents featuring human-like realistic deliberation within social simulation, which include, but are not limited to:
theoretical papers importing insights from human sciences that can be relevant for developing realistic human-like deliberation
modelling papers proposing and testing the suitability of psychology/cognitive science-inspired models in social simulations
methods & engineering papers introducing approaches for validating psychology/cognitive science-inspired agent models and for supporting designers and users in deploying such models (e.g. design tradeoffs)
society-oriented papers detailing how the broader society relates to simulations featuring realistic human-like deliberation, such as responses of system users, narratives, ethical frameworks, critical theories, social impact
structuring papers developing key concepts that are central for the field, supporting the organization of related communities, and identifying venues with high scientific and social prospects
The track welcomes any scientific methodology.
[1] Castelfranchi, C. (2001) The theory of social functions: challenges for computational social science and multi-agent learning. Cognitive Systems Research, 2(1), 5-38.
[2] Edmonds, B. (2012) Context in social simulation: why it can’t be wished away. Computational and Mathematical Organization Theory 18(1), 5-21.
[3] Jensen, M., Lorig, F., Vanhée, L., & Dignum, F. (2021) Deployment and Effects of an App for Tracking and Tracing Contacts During the COVID-19 Crisis. In Social Simulation for a Crisis (pp. 167-188). Springer, Cham.