3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.LG2019★ 3 cited
Adversarial recovery of agent rewards from latent spaces of the limit order book
Jacobo Roa-Vicens, Yuanbo Wang, Virgile Mison +2
Inverse reinforcement learning has proved its ability to explain state-action trajectories of expert agents by recovering their underlying reward functions in increasingly challeng…
cs.LG2019
Towards Inverse Reinforcement Learning for Limit Order Book Dynamics
Jacobo Roa-Vicens, Cyrine Chtourou, Angelos Filos +3
Multi-agent learning is a promising method to simulate aggregate competitive behaviour in finance. Learning expert agents' reward functions through their external demonstrations is…