FAQ: Minimax - The Minimax Function

This community-built FAQ covers the “The Minimax Function” exercise from the lesson “Minimax”.

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Machine Learning

FAQs on the exercise The Minimax Function

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Why does it only tick 8 with ‘X’?
Becuase the outcome of available_moves(x_winning) is [2, 4, 6, 7, 8], doesn’t it have to tick all these 5 numbers with X?

about the variables being pointing to a memory. -
why does it not happen when i do this ?
x= 5
y = x
y = 10
print(x)
print(y)

the output comes out to be 5 and 10. if variable y is set as equal to x, it is merely pointing to a location where value of x is saved! then after changing the value of y, which is at the same location of x, why doesn’t it change the value of x?

If this is so, why copying my_board too new_board has to be done using deepcopy function ?

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Have a look at this answer for a little info-

You’ll find a few arguments over the semantics but Python doesn’t use variables as pointers, they are references (or names) to objects. Pass by assignment where assignment creates a new reference is how the docs refer to it. You may have to search around a bit for an answer that makes sense to you.

For your example your first statement x = 5 assigns x a reference to an integer object. When you use the statement y = x you assign y to reference the same object as x references. When you execute the next statement y = 10 you have a new integer object and you assign y to reference it.

These objects are not altered at any point in this code. All you’ve done is changed what object y references (for ease people sometimes refer to this as just changing the labels assigned to particular objects, or even making an analogy with post-it notes being taken off one object and stuck on another). Even if you now reassigned x, e.g. x = 0 you still haven’t altered the first integer object (5).

For most objects, a reference count of zero would make them open to garbage collection but Python permanently keeps a certain number of integer objects in memory (-5 to 256 I believe). In most cases you can just assume the object will be freed up in memory.

Can you see why deepcopy might be useful then. We do not want to copy the references. We want to copy the objects themselves.

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