CEM: Constrained Entropy Maximization for Task-Agnostic Safe Exploration

Without an assigned task, a suitable intrinsic objective for an agent is to explore the environment efficiently. However, the pursuit of exploration will inevitably bring more safety risks.<br/>An under-explored aspect of reinforcement learning is how to achieve safe efficient exploration when the task is unknown.<br/>In this paper, we propose a...

Safe Reinforcement Learning Applications

Reinforcement Learning (RL) focuses on maximizing the returns (discounted rewards) throughout the episodes, one of the main challenges when using it is that it is inadequate for safety-critical tasks due to the possibility of transitioning into critical states while exploring. Safe Reinforcement Learning (SafeRL) is a subset of RL that focuses...

Safe Online Robust Exploration for Reinforcement Learning Control of Unmanned Aerial Vehicles