Reinforcement Learning-Unit-1

Reinforcement learning is a ____

• 1. Prediction-based learning technique

• 1. Feedback-based learning technique

• 1. History results-based learning technique

• Clustering based learning technique

Which kind of data does reinforcement learning use?

• 1. Labeled data

• 1. UnLabeled data

• None

• Both

Reinforcement learning methods learned through ____?

• 1. Experience

• 1. Predictions

• 1. Analyzing the data

• Classifying the data

Which of the following is the practical example of reinforcement learning?

• 1. House pricing prediction

• 1. Market basket analysis

• 1. Text classification

• 1. Driverless cars

What is an agent in reinforcement learning?

• 1. Agent is the situation in which rewards are being exchanged

• 1. Agent is the simple value in reinforcement learning.

• 1. An agent is an entity that explores the environment.

• An agent is a model in reinforcement learning

What is the environment in reinforcement learning?

• 1. Environment is a situation that is based on the current state

• 1. Environment is a situation in which an agent is present.

• 1. Environment is similar to feedback

• 1. Environment is a situation that the agent returns as a result.

What is the state of reinforcement learning?

• 1. State is a situation in which an agent is present.

• 1. A state is the simple value of reinforcement learning.

• 1. A state is a result returned by the environment after an agent takes an action.

• A state is a value that represents the reward

How many elements does reinforcement learning consist of?

• 2

• 3

• 4

• 5

The agent's main objective is to ____the total number of rewards for good actions.?

• 1. Minimize

• 1. Maximize

• 1. Null

Reinforcement learning is defined by the ____?

• 1. Policy

• 1. Reward Signal

• 1. Value Function

• 1. Model of the environment