Just to clarify a concept as I think 7:29 is not true because value function shouldn't be equal to the Q value. Value function is the expected utility for "all possible actions" at a given state. Therefore, it should be the expected Q_pi rather than just simply equal to Q_pi since Q_pi is the expected utility for "a given action" at a given state. Please correct me if I'm wrong.
he is calculating sum of all rewards you can get. First time sum was 4 as only one reward was present and next was 8 as 2 rewards and then next it was 16 as 4 rewards were there.
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Just to clarify a concept as I think 7:29 is not true because value function shouldn't be equal to the Q value. Value function is the expected utility for "all possible actions" at a given state. Therefore, it should be the expected Q_pi rather than just simply equal to Q_pi since Q_pi is the expected utility for "a given action" at a given state. Please correct me if I'm wrong.
A legacy question from last MDP-1 is still hovering around 2: What is the Transition function for this class? Is it a function of Action?
It is a function of both State and Action.
Somehow Lecture left me confused in the end. may be I should rewatch.
I think there may be a typo at 28:27, it states that the Qpi is (4+8+16)/3 however I believe it should be (4+8+12)/3? Please correct me if I am wrong
I think it should be (4+8+16)/3, as I believe their last run has four 4 values.
he is calculating sum of all rewards you can get. First time sum was 4 as only one reward was present and next was 8 as 2 rewards and then next it was 16 as 4 rewards were there.
Yeah, u really need to be having an episode to play this game
not as good as the previous lecture. harder to follow.