Final answer:
According to the TD model, prediction error (PE) is the difference between reward and Value.
Step-by-step explanation:
According to the TD model, prediction error (PE) is the difference between reward and Value. In reinforcement learning, the TD model (Temporal Difference) is used to predict how much reward an agent will receive based on its actions and the state of the environment. The prediction error is calculated by subtracting the estimated value from the actual reward received.