Reinforcement Learning (RL) Guru

How RL is different from Supervised/Unsupervised learning?

Explain RL by three examples, covering concepts: Agent, Environment, Time step, State space, Action space, Reward, Return, State value, State-action value, Policy, Temporal difference (TD) error, Bellman error, Discount factor, Learning rate, Eligibility factor.

Expain from Markov Processes (MP), Markov Reward Processes (MRP) and Markov Decision Processes (MDP) to RL..

Explain from Multi-Armed Bandits, Contextual Multi-Armed Bandits to Reinforcement Learning