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Reinforcement Learning Example - Autonomous Vehicles
A good way to understand reinforcement learning would be to think about how autonomous vehicles work. Instead of programming all of the rules it should follow (such as road signs, pedestrians, right of way, etc), it is much more easier and efficient to implement a reward/penalty system where the car learns all of the rules that it is supposed to abide by. Furthermore, it would be unreasonable to program individual rules because accidents can happen in unpredictable ways and rules/regulations are always changing and varies in different parts of the world. So, it is much better for autonomous cars to be always learning better ways to make decisions.
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What is the machine's primary goal during the trial-and-error process in reinforcement learning?
Reinforcement learning models keep learning continuously, unlike supervised or unsupervised models.
In reinforcement learning, the machine aims to maximize the total _____ by using lessons from previous attempts.
Match each reinforcement learning term to its correct description.
Order the steps of applying reinforcement learning to a task like flying a helicopter.
Why is reinforcement learning considered more advanced than supervised or unsupervised learning?
Diagnose a poorly designed reward function for an autonomous helicopter landing task.
Why is it difficult to design a good reward function for a reinforcement learning task?
Why might a crashed helicopter trajectory receive a large negative reward like R(T) = -1,000?
The reward function for helicopter trajectories is generated automatically without human input.