most citedImplementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.GT2024

Algorithmic Collusion And The Minimum Price Markov Game

Igor Sadoune, Marcelin Joanis, Andrea Lodi

This paper introduces the Minimum Price Markov Game (MPMG), a theoretical model that reasonably approximates real-world first-price markets following the minimum price rule, such a…

econ.GN2022★ 3 cited

Implementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data

Igor Sadoune, Andrea Lodi, Marcelin Joanis

We present a deep learning solution to address the challenges of simulating realistic synthetic first-price sealed-bid auction data. The complexities encountered in this type of au…