1 citations · 1 across the 3 of their papers we have counts for
4 papers
Linking Homeostasis to Reinforcement Learning: Internal State Control of Motivated Behavior
Naoto Yoshida, Henning Sprekeler, Boris Gutkin
For living beings, survival depends on effective regulation of internal physiological states through motivated behaviors. In this perspective we propose that Homeostatically Regula…
Modelling crypto markets by multi-agent reinforcement learning
Johann Lussange, Stefano Vrizzi, Stefano Palminteri +1
Building on a previous foundation work (Lussange et al. 2020), this study introduces a multi-agent reinforcement learning (MARL) model simulating crypto markets, which is calibrate…
Continuous Time Continuous Space Homeostatic Reinforcement Learning (CTCS-HRRL) : Towards Biological Self-Autonomous Agent
Hugo Laurencon, Yesoda Bhargava, Riddhi Zantye +4
Homeostasis is a biological process by which living beings maintain their internal balance. Previous research suggests that homeostasis is a learned behaviour. Recently introduced…
A bright future for financial agent-based models
J. Lussange, A. Belianin, S. Bourgeois-Gironde +1
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 natu…