The architecture of a model and what it is designed for are not strictly connected to the method of learning. For small AI models for decision making you can absolutely easily write a few hundred examples of actions by your hand and then have a tiny model, that will decide what NPC should do in a simple shooting game. Reinforced learning is just a method of learning, where you can’t or don’t want to provide enough training data, so that you provide and an ability for AI model to learn in a sandbox.
The architecture of a model and what it is designed for are not strictly connected to the method of learning. For small AI models for decision making you can absolutely easily write a few hundred examples of actions by your hand and then have a tiny model, that will decide what NPC should do in a simple shooting game. Reinforced learning is just a method of learning, where you can’t or don’t want to provide enough training data, so that you provide and an ability for AI model to learn in a sandbox.