Let’s start with Ayanokoji’s story!
He quietly sits in class 1-D, observing. He doesn’t ask questions, doesn’t seek attention, yet every move he takes is precise.You may have observed he doesn’t just act at random though he is learns, refine his strategies, and adapt to his environment.
Now, let’s dive into RL!
Before we start exploring, let’s understand what an Agent and an Environment is!
Agent
The agent is the learner or decision-maker. It interacts with the environment, takes actions, and learns from the feedback (rewards/penalties). The interaction is through trial and error while performing actions.
Ayanokoji, analyzing his classmates and making strategic moves.
Environment
The environment is everything the agent interacts with. It provides states, receives the agent’s actions, and gives rewards as feedback.
The Advanced Nurturing High School, full of unpredictable students and hidden rules (for Ayanokoji).
One important note here is, each action executed is without any supervision because that’s how we as human learn (through interaction).
RL is just a computational approach of learning from actions.