GIScience 2020 invites contributions from a wide range of disciplines related to geographic information science, such as geography, earth science, cognitive science, information science, computer science, linguistics, mathematics, philosophy, life sciences, and social science. Topics of interest include agent-based modelling, see https://www.giscience.org/. Deadlines are March 16th (full papers) and May 25th (short papers).
Complexity, understood as the emergence of new macro properties from the interactions of basic components, is a pervasive characteristic in natural, artificial and social systems. The Conference […]
SSC2020 is the 16th annual Social Simulation Conference and will take place at the University of Milan, Italy on 14-18 September 2020. The conference is one of the key activities of the European […]
“Agent Based Modelling for Resilience - Making it happen” is the joint ESSA / DeSIRE Summer School aimed at working on resilience of complex systems.
we call for applications for the BIGSSS Computational Social Science Summer School on Social Cohesion to take place from July 6-17, 2020 in Groningen, the Netherlands generously supported by the […]
SBP-BRiMS is an interdisciplinary computational social science conference focused on both modeling complex socio-technical systems and using computational techniques to reason about and study com[…]
Special Issue of the Springer journal Mind & Society on computational models of human organizational behaviour, meaning behaviour that is not purely individual. Agent-Based Models are welcome.
Please either contact guido.fioretti AT unibo.it, or andrea.ceschi AT univr.it, or andrea.scalco AT abdn.ac.uk.
ESPIn is a 10-day immersive training experience for 25 graduate students, postdoctoral fellows, and/or early career faculty at the CSDMS Integration Facility at the University of Colorado Boulder. ESPIn will offer hands-on training in numerical modeling, best programming practices, open source software development, collaborative coding and version control, Landlab and pymt, high performance computing, and model uncertainty quantification.