COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Supervised Learning
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Unsupervised Learning
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Reinforcement Learning
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None of the above
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Detailed explanation-1: -Reinforcement learning (RL) is an area of machine learning concerned with how intelligent 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.
Detailed explanation-2: -Hence, we can say that “Reinforcement learning is a type of machine learning method where an intelligent agent (computer program) interacts with the environment and learns to act within that.” How a Robotic dog learns the movement of his arms is an example of Reinforcement learning.
Detailed explanation-3: -Reinforcement learning is the closest machine learning type to how humans learn. The algorithm or agent used learns by interacting with its environment and getting a positive or negative reward.
Detailed explanation-4: -Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation.
Detailed explanation-5: -Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones.