MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Reinforcement learning is neither supervised nor unsupervised as it does not require labeled data or a training set. It relies on the ability to monitor the response to the actions of the learning agent. Most used in gaming, robotics, and many other fields, reinforcement learning makes use of a learning agent.

Detailed explanation-2: -Supervised learning requires a labeled dataset for training. Unsupervised learning identifies hidden data patterns from an unlabeled dataset, while Reinforcement learning does not require data as it learns by interacting with the environment.

Detailed explanation-3: -Supervised Learning has two main tasks called Regression and Classification whereas Reinforcement Learning has different tasks such as exploitation or exploration, Markov’s decision processes, Policy Learning, Deep Learning and value learning.

Detailed explanation-4: -Expert-Verified Answer The fourth statement will be considered false as the output used is unknown. The field of machine learning known as reinforcement learning (RL) is concerned with the best course of action for intelligent agents to adopt in a given environment in order to maximize the concept of cumulative reward.