MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Reinforcement learning, which is a close cousin of unsupervised learning, involves giving machines free rein to determine the best course of action in a given situation. But in order to ensure that the system grows, it uses a reward mechanism to reinforce good performance.

Detailed explanation-2: -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-3: -There are two main types of rewards in reinforcement learning: deterministic rewards and stochastic rewards.

Detailed explanation-4: -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-5: -Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation.