COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Decision tree learning
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Reinforcement learning
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Predictive models
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sentiment analysis
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Detailed explanation-1: -In reinforcement learning, the agent is rewarded for taking controls that lead to successful states. The rewards can be immediate, such as receiving a point for each step taken in the right direction, or they can be delayed, such as receiving a point at the end of the episode if the goal was reached.
Detailed explanation-2: -Explanation: Reinforcement learning is the type of learning in which teacher returns reward or punishment to learner.
Detailed explanation-3: -To guide the learning process, reinforcement learning uses a scalar reward signal generated from the environment. This signal measures the performance of the agent with respect to the task goals. In other words, for a given observation (state), the reward measures the effectiveness of taking a particular action.
Detailed explanation-4: -While studying Reinforcement Learning, I have come across many forms of the reward function: R(s, a), R(s, a, s′), and even a reward function that only depends on the current state.