Safe Interactive Model-Based Learning

Understand

Control applications present hard operational constraints.

• A violation of these can result in unsafe behavior.
• This paper introduces Safe Interactive Model Based Learning (SiMBL), a framework to refine an existing controller and a system model while operating on the real environment.
• SiMBL is composed of the following trainable components: a Lyapunov function, which determines a safe set; a safe control policy; and a Bayesian RNN forward model.