MCQ IN COMPUTER SCIENCE & ENGINEERING

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 (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-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.