The correct answer is: D. Utility based agent
A utility-based agent is an agent that makes decisions based on the expected utility of each possible action. Utility is a measure of how good or bad an outcome is, and the expected utility of an action is the average of the utilities of all possible outcomes of that action.
A utility-based agent can deal with happy and unhappy states by assigning different utilities to each state. For example, an agent might assign a utility of 10 to a state where it is happy, and a utility of 0 to a state where it is unhappy. The agent would then choose the action that has the highest expected utility.
A simple reflex agent is an agent that does not have any internal state. It simply reacts to its environment based on the current state. A model-based agent is an agent that has a model of its environment. This model allows the agent to predict how the environment will change in response to its actions. A learning agent is an agent that can learn from experience. This means that it can improve its performance over time by trial and error.
I hope this explanation is helpful. Let me know if you have any other questions.