In the domain of reinforcement learning (RL), a subfield of artificial intelligence, the behavior of an agent is fundamentally shaped by the reward signal it receives during the learning process. This reward signal serves as a critical feedback mechanism that informs the agent about the value of the actions it takes in a given environment.