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cs.LG2021
Mitigation of Adversarial Policy Imitation via Constrained Randomization of Policy (CRoP)
Nancirose Piazza, Vahid Behzadan
Deep reinforcement learning (DRL) policies are vulnerable to unauthorized replication attacks, where an adversary exploits imitation learning to reproduce target policies from obse…
cs.LG2020
Adversarial Attacks on Deep Algorithmic Trading Policies
Yaser Faghan, Nancirose Piazza, Vahid Behzadan +1
Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies. However, DRL have been shown…