9 citations · 16 across the 5 of their papers we have counts for
3 papers · 1 filter
Robust Causal Discovery in Real-World Time Series with Power-Laws
Matteo Tusoni, Giuseppe Masi, Andrea Coletta +3
Exploring causal relationships in stochastic time series is a challenging yet crucial task with a vast range of applications, including finance, economics, neuroscience, and climat…
Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling
Simone Brusatin, Tommaso Padoan, Andrea Coletta +2
Agent-based models (ABMs) are simulation models used in economics to overcome some of the limitations of traditional frameworks based on general equilibrium assumptions. However, a…
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs
Aldo Glielmo, Marco Favorito, Debmallya Chanda +1
Calibrating agent-based models (ABMs) in economics and finance typically involves a derivative-free search in a very large parameter space. In this work, we benchmark a number of s…