5 papers
Verification of Unknown Dynamical Systems via Autoencoder Latent Space
Robert Reed, Luca Laurenti, Morteza Lahijanian
Formal verification provides a powerful framework for proving that dynamical systems satisfy their specifications. However, these techniques face scalability challenges in high-dim…
Learning-Based Shielding for Safe Autonomy under Unknown Dynamics
Robert Reed, Morteza Lahijanian
Shielding is a common method used to guarantee the safety of a system under a black-box controller, such as a neural network controller from deep reinforcement learning (DRL), with…
Error Bounds For Gaussian Process Regression Under Bounded Support Noise With Applications To Safety Certification
Robert Reed, Luca Laurenti, Morteza Lahijanian
Gaussian Process Regression (GPR) is a powerful and elegant method for learning complex functions from noisy data with a wide range of applications, including in safety-critical do…
Shielded Deep Reinforcement Learning for Complex Spacecraft Tasking
Robert Reed, Hanspeter Schaub, Morteza Lahijanian
Autonomous spacecraft control via Shielded Deep Reinforcement Learning (SDRL) has become a rapidly growing research area. However, the construction of shields and the definition of…
Promises of Deep Kernel Learning for Control Synthesis
Robert Reed, Luca Laurenti, Morteza Lahijanian
Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising to…