Practice - Components: States (S), Actions (A), Transition probabilities (P), Rewards (R), and Discount factor (γ)
Practice Questions
Test your understanding with targeted questions
What do we mean by 'States' in an MDP?
💡 Hint: Think about different positions in a game.
What denotes the chance of transitioning from one state to another?
💡 Hint: Relate it to the dynamics of the game environment.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What do 'States' in an MDP refer to?
💡 Hint: Consider different contexts the agent is navigating.
True or False: The Discount Factor, γ, helps prioritize immediate rewards over future rewards.
💡 Hint: Think about how long-term strategies are valued.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Given a simple MDP with three states and two actions, define potential Transition Probabilities based on the expected behavior of an agent. Explain your reasoning.
💡 Hint: Consider realistic scenarios where actions do not always lead to the preferred outcome.
You are tasked with designing an RL system for a self-driving car. Describe how you would set the Rewards and Discount Factor parameters to maximize safe long-term navigation.
💡 Hint: Think about long-term goals like safety and efficiency versus short-term benefits like speed.
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Reference links
Supplementary resources to enhance your learning experience.