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Reinforcement Learning
REINFORCEMENT LEARNING Reinforcement learning ( RL ) is an area of machine learning concerned with how software agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning . without some feedback about what is good and what is bad, the agent will have no grounds for deciding which move to make. The agent needs to know that something good has happened when it (accidentally) checkmates the opponent, and that something bad has happened when it is checkmated-or vice versa, if the game is suicide chess. This kind of feedback is called a reinforcement or reward. Rewards served to define optimal policies in Markov decision processes (MDPs). An optimal policy is a policy that maximizes the expected total reward. The task of reinforcement learn...
