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Consider the famous Snake game. The player here is an autonomous agent. The player controls the game with four controls - up , down,left, right.

Consider the famous Snake game. The player here is an autonomous
agent. The player controls the game with four controls - up, down,left,
right. There will be food anywhere on the screen.The food disappears in
10 secs. The player has to control the snake in a way it eats food and he
has to avoid the frames borders otherwise the snake dies.Each time the
snake eats food, the body length of the snake is increased. During the
game the player has also to avoid the snakes body otherwise the game
terminates, as well. The rewards are Eat food =+10, Game over =-10,
else =0. Make the required assumptions and state them clearly.Consider the famous Snake game. The player here is an autonomous
agent. The player controls the game with four controls - up, down,left,
right. There will be food anywhere on the screen.The food disappears in
10 secs. The player has to control the snake in a way it eats food and he
has to avoid the frames borders otherwise the snake dies.Each time the
snake eats food, the body length of the snake is increased. During the
game the player has also to avoid the snakes body otherwise the game
terminates, as well. The rewards are Eat food =+10, Game over =-10,
else =0. Make the required assumptions and state them clearly. (i) Write down an MDP formulation for the given scenario with an explanation for all design
choices. [3 M]
(ii) After some time you find the game not progressing with the rewards. What can go wrong?
[1 M]
(iii) Your initial reward is 0 followed by infinite 10s. What is the initial and the next expected
return ? Let the discount rate be 0.4[2 M]
(iv) Suppose you treated this as an episodic task but also used discounting, with all rewards
zero except for 1 upon failure. What then would the return be at each time? How does this
return differ from that in the discounted, continuing formulation of this task?

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