An ongoing conversation with a system
Feedback closes the distance between what a model expects and what actually happens. Control asks how actions can shape the next state.
Model Predictive Control, reinforcement learning, and agent environments offer different ways into this loop. The shared interest is in systems that keep adjusting, with attention to both their models and their consequences.
A working entry. The connections may change.