Reinforcement Learning and Deep RL Python Theory and Projects - How to Get State

The video tutorial explains the implementation of a 'get state' function, which manages the current state of a screen in a program. It introduces the 'get processed screen' function, which is yet to be implemented, and discusses creating a black screen using Torch. The tutorial also covers handling intermediate states and using state differences for processing, particularly in the context of feeding data to a policy network.

What will happen if the state is neither a starting nor an ending state?

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Describe the process of how the difference between two states is calculated.

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