model-based-learning

This paper presents a novel model-based reinforcement learning algorithm that leverages Bayesian methods and Linear Temporal Logic specifications for efficient policy synthesis in unknown environments, demonstrating improved sample efficiency and safety compared to traditional approaches.

This paper presents a model-based reinforcement learning approach for autonomous droplet navigation in microfluidic platforms, achieving reliable navigation through complex geometries with zero-shot transfer from simpler paths.