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Found 5 papers, 1 papers with code
Augmenting Offline RL with Unlabeled Data
This framework enables the student policy to gain insights not only from the offline RL dataset but also from the knowledge transferred by a teacher policy.
Integrating Domain Knowledge for handling Limited Data in Offline RL
With the ability to learn from static datasets, Offline Reinforcement Learning (RL) emerges as a compelling avenue for real-world applications.
Counterexample Guided RL Policy Refinement Using Bayesian Optimization
The first component is an approach to discover failure trajectories using Bayesian optimization over multiple parameters of uncertainty from a policy learnt in a model-free setting.
Hierarchical Program-Triggered Reinforcement Learning Agents For Automated Driving
Recent advances in Reinforcement Learning (RL) combined with Deep Learning (DL) have demonstrated impressive performance in complex tasks, including autonomous driving.
Semi-Lexical Languages -- A Formal Basis for Unifying Machine Learning and Symbolic Reasoning in Computer Vision
Human vision is able to compensate imperfections in sensory inputs from the real world by reasoning based on prior knowledge about the world.
