In what way do game theory and machine learning decision making differ?

Group of answer choices

Game theory relies solely on mathematical models to predict outcomes, whereas machine learning decision making incorporates both mathematical models and real$-$world data to make decisions.

Game theory focuses on analyzing strategic interactions between rational decision$-$makers, while machine learning decision making primarily involves training algorithms to learn patterns and make predictions from data.

Game theory emphasizes the role of randomness and uncertainty in decision$-$making scenarios, while machine learning decision making seeks to minimize uncertainty by learning from historical data.

Game theory is primarily concerned with optimizing individual decision$-$making strategies, while machine learning decision making aims to optimize system performance by iteratively improving algorithms through training.