The working of reinforcement learning can be understood by the below diagram:
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The RL-based system mainly consists of the following components:
1) Environment: The environment is the surrounding of the agent, where he needs to explore and act upon.
2) Agent: The agent is the Artificial Intelligence program that has sensors and actuators and the ability to perceive the environment.
3) State: It is the situation that is returned by the environment to the agent.
4) Reward: The feedback received to the agent after doing each action.
In RL, the agent interacts with the environment in order to explore it by doing some actions. On each action, the state of agent gets changed or sometimes remArtificial Intelligencens the same, and based on the type of action, and he gets a reward. The reward is feedback, which may be negative or positive based on the action.
The goal of the agent is to maximize the positive reward and to achieve the goal of the problem.
