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

Asymptotic Analysis of Sample-Averaged Q-Learning

Abstract: Reinforcement learning (RL) has emerged as a key approach for training agents in complex and uncertain environments. Incorporating statistical inference in RL algorithms is essential for ...
GitHub

Gymnasium RL Agent Training Loop

A complete, runnable implementation of the reinforcement learning training loop using the Gymnasium library. An agent learns to play Blackjack by trying different actions, observing the results, and ...
IEEE

Optimal Secure Control for Cyber-Physical Systems Under False Data Injection Attacks via Incremental Iterative Q-Learning Algorithm

Abstract: An incremental iterative Q-learning algorithm (IIQLA) is proposed to tackle the optimal secure control problem for cyber-physical systems under false data injection attacks. Within a ...