IEEE

Deep Reinforcement Learning for Dependent Task Offloading in Multi-Access Edge Computing

Abstract: Multi-access Edge Computing (MEC) is an emerging and promising computing paradigm that distributes computational resources closer to users at the network edge, effectively reducing both ...
marktechpost

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
IEEE

A Novel Multi-Objective Deep Q-Network: Addressing Immediate and Delayed Rewards in Multi-Objective Q-Learning

Abstract: Current multi-objective reinforcement learning (MORL) research often struggles to balance multiple objectives and manage the stability and performance of learning algorithms, especially in ...