@inproceedings{d13577f44a04422db2521edc45eaaf4f,
title = "Learning and cognition in financial markets: A paradigm shift for agent-based models",
abstract = "The history of research in finance and economics has been widely impacted by the field of Agent-based Computational Economics (ACE). While at the same time being popular among natural science researchers for its proximity to the successful methods of physics and chemistry for example, the field of ACE has also received critics by a part of the social science community for its lack of empiricism. Yet recent trends have shifted the weights of these general arguments and potentially given ACE a whole new range of realism. At the base of these trends are found two present-day major scientific breakthroughs: the steady shift of psychology towards a hard science due to the advances of neuropsychology, and the progress of reinforcement learning due to increasing computational power and big data. We outline here the main lines of a computational research study where each agent would trade by reinforcement learning.",
keywords = "Agent-based models, Financial markets, Multi-agent systems, Reinforcement learning",
author = "Johann Lussange and Alexis Belianin and Sacha Bourgeois-Gironde and Boris Gutkin",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2021.; Intelligent Systems Conference, IntelliSys 2020 ; Conference date: 03-09-2020 Through 04-09-2020",
year = "2021",
doi = "10.1007/978-3-030-55190-2_19",
language = "American English",
isbn = "9783030551896",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "241--255",
editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",
booktitle = "Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference IntelliSys Volume 3",
address = "Netherlands",
}