The type of machine learning which allows the model to learn by exploring the environment and receiving rewards or punishments for certain actions is known as—

Correct option is D

The correct answer is (d)  Reinforcement Learning
Explanation: •  Reinforcement Learning is a type of machine learning concerned with how intelligent agents should take  actions in an environment. • The model learns through a system of  rewards (for good actions) and  punishments (for bad actions). • The goal is to learn an optimal policy that maximizes the total cumulative reward. • This approach does not require labeled data; instead, it learns through  trial and error. • It is used in areas like robotics, game playing (e.g., AlphaGo), and autonomous vehicles.
Information Booster: •  Agent: The learning entity that makes decisions and takes actions in an environment. •  Environment: The external system where the agent operates. •  Reward/Punishment: Feedback from the environment guiding the learning process.
Additional Knowledge: (a)  Supervised Learning: Involves training a model on a  labeled dataset (input-output pairs) to make predictions. (b)  Unsupervised Learning: Involves training a model on an  unlabeled dataset to find patterns, structures, and relationships within the data. (c)  Refurbished Learning: This is  not a standard term or type of machine learning.