Adversarial recovery of agent rewards from latent spaces of the limit order book

• Published in: IDEAS Working Paper Series from RePEc
• Main Authors: Roa-Vicens, Jacobo, Wang, Yuanbo, Mison, Virgile, Yarin Gal, Silva, Ricardo
• Format: Paper
• Language: English
• Published: St. Louis Federal Reserve Bank of St. Louis 01.01.2019
• Subjects: Algorithms

Inverse reinforcement learning has proved its ability to explain state-action trajectories of expert agents by recovering their underlying reward functions in increasingly challenging environments. Recent advances in adversarial learning have allowed extending inverse RL to applications with non-sta...