IEEE

Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning Assisted Federated Learning

Abstract: The rapid growth of industrial Internet of Things (IIoT) applications generates massive amount of heterogeneous data that are prone to cyberattacks. The imperative is to secure industrial ...
Frontiers

Solving robotics tasks with prior demonstration via exploration-efficient deep reinforcement learning

This paper proposes an exploration-efficient deep reinforcement learning with reference (DRLR) policy framework for learning robotics tasks incorporating demonstrations. The DRLR framework is ...
Frontiers

LG-H-PPO: offline hierarchical PPO for robot path planning on a latent graph

The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...
IEEE

Safe Reinforcement Learning via Episodic Control

Abstract: Safe reinforcement learning (Safe RL) aims to learn policies capable of learning and adapting within complex environments while ensuring actions remain free from catastrophic consequences.