GAMA is an easy-to-use open-source modelling and simulation environment for creating spatially explicit agent-based simulations. This workshop introduces the platform, the dedicated language called Gaml, and its resources (online documentation, tutorials, and more) to help you start your project powered by Gama.

Requirements: Laptop with capacity to install GAMA

Organisers: Bruce Edmonds, Cezara Pastrav, Sofia Karlsson, Frank Dignum

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. 

Organisers: Rok Novak, Zuzanna Kurowska, Deniz Sirin

Communicating social simulation research poses specific challenges, from explaining model structure and assumptions to conveying uncertainty and relevance to non-expert audiences. Building on the goals of a proposed  Special Interest Group within the European Social Simulation Association, the workshop combines shared exploration with emerging guidance.

This three-hour workshop (using Python) introduces participants to simulation-based inference and its applications to complex social models, bridging the gap between agent-based simulations and experimental research.

ESSA@work participants present a model they are working on to gather feedback and suggestions to improve, adapt and/or extend their model.

GAMA is an easy-to-use open-source modelling and simulation environment for creating spatially explicit agent-based simulations. This workshop introduces how to use GIS data for simulation in GAMA. During this 3-hour workshop, a model of urban mobility & planning will support the training based on Gaml reusable building blocks.

Requirements: Laptop with capacity to install GAMA (and attendance at introduction workshop or equivalent experience)

Models of human decision (MOODs) are a central component of agent-based social simulation (ABSS) that raises a variety of open ended questions investigated by the ABSS community as well as by  connected ones (e.g., affective computing, intelligent virtual agents). This workshop is meant to discuss practical insights based on experience or joint interests and aspects on which members of our community could collaborate.

ESSA@work participants present a model they are working on to gather feedback and suggestions to improve, adapt and/or extend their model.

Reproducible Workflows for Social Simulation Leveraging Exponential Random Graph Models (ERGMs) for Agent-Based Models (ABMs)

Requirements: Familiarity with logistic regression, experience fitting logistic model in R will help.

Empirical agent-based modelling is a key use case for national HPC (high-performance computing) infrastructure. Kay Yeung, from UKRI, will be sharing updates on UKRI’s vision of the national compute ecosystem and compute investments, and is keen to meet researchers in the social sciences to explore barriers to accessing local and national infrastructure.