7 citations · 10 across the 4 of their papers we have counts for
4 papers
Studying and improving reasoning in humans and machines
Nicolas Yax, Hernan Anlló, Stefano Palminteri
In the present study, we investigate and compare reasoning in large language models (LLM) and humans using a selection of cognitive psychology tools traditionally dedicated to the…
Stock market microstructure inference via multi-agent reinforcement learning
J. Lussange, I. Lazarevich, S. Bourgeois-Gironde +2
Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS). These statistical tools are based on modelling age…
Mesoscale impact of trader psychology on stock markets: a multi-agent AI approach
J. Lussange, S. Palminteri, S. Bourgeois-Gironde +1
Recent advances in the fields of machine learning and neurofinance have yielded new exciting research perspectives in practical inference of behavioural economy in financial market…
Stock price formation: useful insights from a multi-agent reinforcement learning model
J. Lussange, S. Bourgeois-Gironde, S. Palminteri +1
In the past, financial stock markets have been studied with previous generations of multi-agent systems (MAS) that relied on zero-intelligence agents, and often the necessity to im…