marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
IEEE

Deep Q-Learning with Gradient Target Tracking

Abstract: This paper introduces Q-learning with gradient target tracking, a novel reinforcement learning framework that provides a learned continuous target update mechanism as an alternative to the ...
IEEE

CoQGR: A collaborative routing strategy integrating Q-learning and cooperative game theory for large-scale LEO satellite constellations

Abstract: Traditional routing techniques face considerable challenges in large-scale Low Earth Orbit (LEO) satellite networks for Internet of Things (IoT) data backhaul, such as slow convergence speed ...