This review synthesizes existing RL-MPC integration methods for linear systems into a taxonomy across RL roles, algorithms, MPC formulations, costs, and domains while identifying recurring patterns and practical challenges.
Lapan, Deep Reinforcement Learning Hands-On: A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF, Packt Publishing, Birmingham
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A Systematic Review and Taxonomy of Reinforcement Learning-Model Predictive Control Integration for Linear Systems
This review synthesizes existing RL-MPC integration methods for linear systems into a taxonomy across RL roles, algorithms, MPC formulations, costs, and domains while identifying recurring patterns and practical challenges.