Reinforcement Learning – Reward for Learning

RL compared with a scenario like "how some new born baby animals learns to stand, run, and survive in the given environment." Reinforcement Learning (RL) is more general than supervised learning or unsupervised learning. It learn from interaction with environment to achieve a goal or simply learns from reward and punishments. In other words algorithms learns to react to the environment. TD-learning seems to be closest to how humans learn in this type of situation, but Q-learning and others also have their own advantages.