Learn in the textbookThe Framework of Machine Learning
DefinitionReinforcement learning (強化学習) is a method that uses the reward received as a result of an action (a score that grows as the result improves) as its clue, and learns by trial and error how to act so the reward gets larger.
ExplanationIt repeats the cycle of acting and getting a result many times, looking for actions that make the total reward large over the long run, not just the immediate reward. It is used for choosing moves in board games and for controlling robots so they walk without falling.
AnalogyIt is like learning to ride a bicycle with no one teaching you the steps, adjusting how you use your body by the feel of how far you got without falling.
Memory hook"Reinforcement" is a psychology term for how behavior that gets praised is repeated more often. Remember it as strengthening actions with rewards.