Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define what an agent is in Reinforcement Learning.
💡 Hint: Think about who is making decisions in this context.
Question 2
Easy
What does the environment refer to in this section?
💡 Hint: Consider the surroundings of the agent.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does the term 'agent' refer to in Reinforcement Learning?
- The learner
- The environment
- The reward function
💡 Hint: Think about who is acting in the learning process.
Question 2
The current situation of the agent is referred to as the...
💡 Hint: It's what the agent perceives before taking an action.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a simple RL algorithm to demonstrate how an agent might learn to prefer one route over others in a traffic simulation.
💡 Hint: Think about how to represent states and calculate rewards!
Question 2
Analyze how sparse rewards can affect an agent's learning path in a maze-solving scenario.
💡 Hint: Consider the implications of not having rewards at every step.
Challenge and get performance evaluation