Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification

Understand

The fields of MPC and RL consider two successful control techniques for Markov decision processes.

• Both approaches are derived from similar fundamental principles, and both are widely used in practical applications, including robotics, process control, energy systems, and autonomous driving.
• Despite their similarities, MPC and RL follow distinct paradigms that emerged from diverse communities and different requirements.
• Various technical discrepancies, particularly the role of an environment model as part of the algorithm, lead to methodologies with nearly complementary advantages.