EMERGING TRENDS IN COMPUTING
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Learning from labeled data
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Learning from unlabeled data
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Learning from environment
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None of the above
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Detailed explanation-1: -Reinforcement Learning is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions and seeing the results of actions. For each good action, the agent gets positive feedback, and for each bad action, the agent gets negative feedback or penalty.
Detailed explanation-2: -The environment of the reinforcement learning is important to training learning. A good environment can speed up training, reduce costs, and better test new RL algorithms.
Detailed explanation-3: -Reinforcement Learning (RL) is a general framework for adaptive control that enables an agent to learn to maximize a specified reward signal through trial and error using feedback from its actions and experiences, i.e., actively interacting with the environment by taking actions and observing the reward.