[agents] Social Simulation Conference Special track: Sense & Sensibility: Modelling human deliberation and decision-making

[Loïs Vanhée]

***Apologies for cross-posting.***

Dear colleagues,

If you are working with making more realistic models of human deliberation, please consider submitting your full articles, short papers/extended abstracts, and/or posters to the special track "Sense & Sensibility: Modelling human deliberation and decision-making" at the Social Simulation Conference (4-8 September, Glasgow, UK).

Submission link: <https://ssc2022.behavelab.org/submissions/> https://ssc23-sphsu.online/74-2/

Deadline: April 28th 2023

For details of the call, see below the signature.

This special track is supported by the ESSA SIG Games and Agent-based models (contact: Melania or Timo).

Looking forward to receiving your contributions,

Loïs, Carole, Melania, and Timo.

Special track: Sense & Sensibility: Modelling human deliberation and decision-making

Track chairs:

Loïs Vanhée, Umeå University, Sweden

Carole Adam, Université Grenoble Alpes, France

Melania Borit, UiT the Arctic University of Norway

Timo Szczepanska, UiT the Arctic University of Norway


As replicating human-like decisions is at the core of agent-based modelling for social simulation, we need theories, models, and methods for building agents that reproduce authentic and realistic features of human deliberation (e.g. the more deprived is a need, the greater is the corrective action) while fitting within the constraints and purposes set by social simulations (e.g. covering specific social phenomena, scalability).

The current prevailing approach to model human decision-making in social simulation revolves around random distributions of behaviors, which reduces both the spectrum of possible simulations to cases where decisions can be simplified to distributions and the accuracy of simulations as psychological incoherences and subsequent wrong conclusions can be introduced [1,2,3]. If we want to step up social simulation for improving both the range of phenomena we can cover and the realism of our models, we need our models to be further ingrained in the findings identified by psychology and cognitive sciences. However, the question of how to produce such models and how to balance the extra expenses they entail (e.g. complexity, validation, computational costs) with simulation benefits (e.g. realism, explainability) remain open and is the subject of this track.

This track is open to all approaches seeking to introduce human-like realism of decision-making within social simulation, which include but are not limited to:

  *   theoretical papers introducing theoretical foundations from human sciences and explaining how they can be integrated within social simulation
  *   modelling papers proposing and testing the suitability of psychology-inspired models in social simulations
  *   methods & engineering papers introducing support for designers for deciding upon what and how to implement and use human-like agent deliberation processes in practice
  *   survey papers reviewing models formerly produced in the (social simulation) field and identifying their strengths and weaknesses and pathways for improvement
  *   visions papers identifying areas in society and psychology feature where social simulation can achieve high impact should such a feature be available

 [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, Bruce. "Context in social simulation: why it can't be wished away." Computational and Mathematical Organization Theory 18.1 (2012): 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.

-------------------------

Loïs Vanhée, Ph.D.

Associate professor

Responsible Artificial Intelligence<https://www.umu.se/en/research/groups/responsible-artificial-intelligence/> team

Department of Computing Science<https://www.umu.se/en/department-of-computing-science/>

Umeå University

Umeå, Sweden

E-mail: lois.vanhee at umu.se<mailto:lois.vanhee at umu.se>

Web: https://www.umu.se/en/staff/lois-vanhee/


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