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 algorithm
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Unsupervised learning algorithm
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Semi-supervised learning algorithm
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Reinforcement learning algorithm
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Detailed explanation-1: -Explanation: Reinforcement learning is the type of learning in which teacher returns reward or punishment to learner.
Detailed explanation-2: -Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.
Detailed explanation-3: -Reinforcement learning is all about gamifying the learning process. This type of machine learning uses a reward-penalty method to teach an AI system. If it makes the right move, it gets rewarded. If it makes a mistake, it receives a penalty.
Detailed explanation-4: -Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones. In general, a reinforcement learning agent is able to perceive and interpret its environment, take actions and learn through trial and error.
Detailed explanation-5: -Trial-and-error learning is connected with the so-called long-term reward. This reward is the ultimate goal the agent learns while interacting with an environment through numerous trials and errors. The algorithm gets short-term rewards that together lead to the cumulative, long-term one.