Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies
Sampo Kuutti,Saber Fallah,Richard Bowden,Sampo Kuutti,Saber Fallah,Richard Bowden
Deep learning has become an increasingly common technique for various control problems, such as robotic arm manipulation, robot navigation, and autonomous vehicles. However, the downside of using deep neural networks to learn control policies is their opaque nature and the difficulties of validating their safety. As the networks used to obtain state-of-the-art results become increasingly deep and ...
