Community Events

Invitation to demonstrate your latest developments in agent-based software and robotic systems at the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024) to be held in Auckland, New Zealand, on May 6-10, 2024.

AAG2024|Second Call for Abstracts: Geosimulations for Addressing Societal Challenges

ABM based presentation opportunities at AAG 2024 conference

Interested in learning about the climate system and acquiring computational skills to access, analyze, and visualize climate data? Join Climatematch Academy as a student for our two week virtual program, where you will learn from world-class climate experts and collaborate on team projects with fellow students. Prior experience with climate science is not necessary, however familiarity with a coding language is required.

Co-located with the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), the international workshop on Interdisciplinary Design of Emotion Sensitive Agents (IDEA) se[…]

The Covid-19 pandemic has triggered a large wave of fresh research on epidemiological models, both using traditional equation-based approaches as well as more modern approaches such as agent-base[…]

Computational simulation provides an inexpensive and time efficient means of carrying out what-if scenarios and studies into alternative strategies for a given situation. Furthermore, it enables […]

UiT The Arctic University of Norway, The Faculty of Biosciences, Fisheries and Economics (BFE) has a position available for a Doctoral Research Fellow in fishing and aquaculture technology. The p[…]

The GeoSim 2022 workshop focuses on all aspects of geospatial simulation as a paradigm to understand, model, and predict spatial phenomena and aid decision making. New simulation methodologies an[…]

Taught by Prof. Dr. Petra Ahrweiler (Mainz University; president of ESSA) and Dr. Corinna Elsenbroich (Glasgow University), the course “Policy Modelling” focuses on the substantive problems, theories, and related computational models in a number of core areas of policy modelling. Participants learn to bridge the gap between policy practice and formal models by applying complexity-sensitive computational methods (especially agent-based modelling) using Netlogo and Python.