AIMS AND SCOPE:
Evolutionary game theory (EGT) and agent-based modelling (ABM) are proven approaches with a long history of success in many related fields such as economics, biology, physics, computer science and political science. The mathematical tools of EGT are particularly suitable for analysing small to medium-scale dynamical models, while ABM methods enable extensive simulations of large-scale complex systems. The combination of these two complementary approaches has been widely and successfully adopted to provide insights into both classical domains such as explaining the emergence of social and collective behaviours and pressing challenges such as climate change, inequalities, technological safety, etc.
This special session aims to bring together researchers that apply the combination of ABM and EGT to both classical and novel, emerging application domains. We invite submissions of original, previously unpublished papers with topics on, but not limited to, the following:
- Evolution of social and collective behaviours
- Evolutionary game models of emotion and cognitive agents
- Evolutionary game models of climate change interaction
- Evolutionary dynamics of technological innovation
- Evolutionary models of technology adoption
- Collective risk games dynamics
- Agent-based modeling
- Individual-based simulation
- Multi-agent systems
Special session papers should be uploaded online through the paper submission website of IEEE WCCI 2020. Please select the corresponding special session name as the “main research topic” in submission. For the latest information on important dates, please refer to this page.
- Submission deadline: 15 January 2020
- Notification: 15 March 2020
- Final paper submission: 15 April 2020
- Raymond Chiong (The University of Newcastle, Australia)
- The Anh Han (Teesside University, UK)
- Francisco C. Santos (Instituto Superior Tecnico, Portugal)
- Manuel Chica (University of Granada, Spain)
Raymond Chiong is a tenured academic at the University of Newcastle, Australia. He is also a visiting scholar with Tsinghua University, China, and a guest research professor with Huazhong University of Science and Technology, China. He obtained his PhD degree from the University of Melbourne, Australia. He has been actively pursuing research related to evolutionary game theory, optimisation, data analytics, and modelling of complex adaptive systems for many years. He is currently the Editor-in-Chief of the Journal of Systems and Information Technology, an Editor of Engineering Applications of Artificial Intelligence, and an Associate Editor of the IEEE Computational Intelligence Magazine. He has also served in a Guest Editor role for a number of reputable international journals, such as the International Journal of Production Economics and European Journal of Operational Research. To date, he has produced/co-authored over 160 refereed publications in the form of books, book chapters, journal articles and conference papers, among others.
THE ANH HAN
The Anh Han is a Reader (Associate Professor) in Computer Science, Teesside University (UK), since 2014. Before that, he obtained his PhD in Computer Science from the New University of Lisbon (Portugal), in 2012, followed by two years as an FWO postdoctoral fellow at the AI Lab, Vrije Universiteit Brussel (Belgium). His current research interests span across a wide range of topics within artificial intelligence (AI) and multidisciplinary research, including dynamics of human cooperation, evolutionary game theory, AI cognitive modelling, agent-based modelling, behavioural economics, intention recognition, and knowledge representation and reasoning. More information, including awards and publications, can be found at https://www.scedt.tees.ac.uk/t.han/
FRANCISCO C. SANTOS
Francisco C. Santos is an associate professor with the Department of Computer Science of Instituto Superior Técnico (IST), University of Lisbon, Portugal. He is also a senior researcher at the Group on Artificial Intelligence for People and Society (GAIPS/INESC-ID). He received a PhD in Computer Science from the Université Libre de Bruxelles (IRIDIA, ULB). After his PhD, he was Chargé de Recherches at the Machine Learning Group of ULB (MLG, Brussels), and a senior researcher at the Centre for Artificial Intelligence of NOVA-Lisbon. His research interests are in the application and development of computational tools to understand how collective patterns emerge and are maintained at population and ecosystem levels. He works on algorithms for dealing with large-scale population dynamics and complex networks, with applications in evolutionary biology, human cooperation and social norms, environmental governance, and urban dynamics. He was awarded the 2017 Young Scientist Award for Socio-Econophysics of the German Physical Society, and the 2016 CDG-University of Lisbon prize in Computer Science. He is a junior fellow of the Lisbon Academy of Sciences, and serves as an associate editor for several scientific journals.
Manuel Chica, BSc, MSc, PhD in Computer Science, is currently a “Ramón y Cajal” Senior Researcher at the University of Granada, granted by the Spanish government, and the Chief A.I. Officer and scientific partner for ZIO, an SME applying computational intelligence and agent-based modelling to marketing. Additionally, he is a conjoint lecturer at the University of Newcastle, Australia, after being a post-doctoral Endeavour Research Fellow there. His main research interests include agent-based modelling, evolutionary game theory, multi-objective optimisation, bio-inspired metaheuristics, applied data science, and marketing. He is a co-inventor of an international patent under exploitation and has published more than 80 peer-reviewed scientific papers (31 of them in JCR-indexed journals, most of them in the first quartile, being the first author in 18 of them). He has also participated in 18 research projects, playing the role of Principal Investigator in 2 European FP7s, 3 National projects, and 4 research contracts, with fundings of more than 3 million euros in total. See http://www.manuchise.com for more details.