GitHub

double-q-learning

Implemented Behavior Cloning, DAgger, Double Q-Learning, Dueling DQN, and Proximal Policy Optimization (PPO) in a simulated environment and analyzed/compared their performance in terms of efficiency, ...
IEEE

Machine Learning Approaches for Process Automation: A Case Study Using Q-Learning and Supervised Learning

Abstract: Process automation is critical in modern industries, providing systems for precise control of variables such as temperature, pressure, and flow. Traditional control methods like PID ...
Scientific Research Publishing

Kumar, A., Zhou, A., Tucker, G. and Levine, S. (2020) Conservative Q-Learning for Offline Reinforcement Learning. Advances in Neural Information Processing Systems, 33, 1179-1191.

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
GitHub

q-learning

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3 ...
IEEE

Multi-Objective Adaptive Traffic Signal Control Using Fuzzy Control and Q-Learning

Abstract: A multi-objective adaptive traffic signal control algorithm using fuzzy control and Q-learning was proposed to improve the efficiency, traffic safety, and operational stability of signalized ...