Workshops

Workshop Details

Organizers

Website

XIV Workshop on Agents Applied in Healthcare (A2HC) Sara Montagna, Stefano Mariani, Gaetano Manzo, and Michael Ignaz Schumacher

https://a2hc.github.io/a2hc2022/

Adaptive and Learning Agents (ALA) Felipe Leno Da Silva, Conor Hayes, Fernando Santos, and Francisco Cruz https://ala2022.github.io/
The 4th Games, Agents, and Incentives Workshop (GAIW) Ben Abramowitz, Sofia Ceppi, John P. Dickerson, Hadi Hosseini, Omer Lev, Nicholas Mattei, and Yair Zick https://preflib.github.io/gaiw2022/
Workshop on Optimization and Learning in Multi-Agent Systems (OptLearnMAS) Hau Chan, Ferdinando Fioretto, and Jiaoyang Li https://optlearnmas22.github.io/
The 23rd International Workshop on Multi-Agent-Based Simulation (MABS) Fabian Lorig and Emma Norling https://mabsworkshop.github.io/
Workshop on Learning with Strategic Agents (LSA) Nicholas Bishop, Minbiao Han, Hanrui Zhang, Haifeng Xu, and Long Tran-Thanh https://minbiaohan.github.io/LSA/
International Workshop on Coordination, Organizations, Institutions, Norms and Ethics for Governance of Multi-Agent Systems (COINE) Bastin Tony Roy Savarimuthu, Nirav Ajmeri, and Andreasa Morris-Martin https://coin-workshop.github.io/coine-2022-auckland/
Agent-Based Modeling of Urban Systems (ABMUS) Jason Thompson, Koen van Dam, Minh Kieu, Alison Heppenstall, Jiaqi Gee, and Nic Malleson http://abmus.github.io/
The 3rd International Workshop on Autonomous Agents for Social Good (AASG) Kai Wang, Amulya Yadav, Kayse Maass, and Aparna Taneja

https://guaguakai.github.io/aasg2022/

Autonomous Robots and Multirobot Systems (ARMS) Francesco Amigoni and Noa Agmon https://u.cs.biu.ac.il/~agmon/arms2022/
Engineering Multi-Agent Systems Workshop (EMAS) Rym Z. Wenkstern, Amit Chopra, and Jurgen Dix

https://emas.in.tu-clausthal.de/2022

4th International Workshop on EXplainable and TRAnsparent AI and Multi-Agent Systems (EXTRAAMAS) Davide Calvaresi, Amro Najjar, Kary Främling, and Michael Winikoff https://extraamas.ehealth.hevs.ch/
Rebellion and Disobedience in Artificial Intelligence (RaD-AI) David W. Aha, Reuth Mirsky, and Peter Stone https://sites.google.com/view/rad-ai/home