Question 19
Domain 1 — AI Concepts, Terminology, and Use CasesWhat type of AI involves machines that learn from rewards and penalties to achieve a goal?
Correct answer: C
Explanation
Reinforcement learning is the AI approach where an agent learns by interacting with an environment and receiving rewards or penalties. It uses those feedback signals to improve actions over time and achieve a goal.
Why each option is right or wrong
A. Unsupervised learning
B. Supervised learning
C. Reinforcement learning
Reinforcement learning is the branch of machine learning in which an agent improves its policy by trial-and-error interaction with an environment, using reward signals to reinforce desirable actions and penalty signals to discourage undesirable ones. In standard AI taxonomy, this distinguishes it from supervised learning (which relies on labeled examples) and unsupervised learning (which finds patterns without feedback), so the presence of rewards and penalties points specifically to reinforcement learning.
D. Deep learning