Learning Stock Trading Policies via Barycenter-Based Adversarial Inverse Reinforcement Learning

arXiv:2608. 15770v1 Announce Type: new Abstract: Designing effective trading strategies using reinforcement learning remains challenging due to delayed and noisy rewards, poor exploration, and the difficulty of enforcing explicit risk constraints.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

• reinforcement-learning
• safety