data:image/png;base64,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data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeAAAAFoCAYAAACPNyggAAACtUlEQVR4nO3BMQEAAADCoPVPbQwfoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA+Bo3+AAF/RMkcAAAAAElFTkSuQmCC10101010LABEL will stamp text on the stage at the given font size. The direction of the text is the direction the sprite is facing, and color will match the pen color.Hello!121datamapmany1data lists11110i121cont3catchtagcontcatchtagSpriteSprite-9015018050J13150050-500503Win13x3EmptyXScore0OScore0i1Begin the recursive iteration, for each of the squares that are emptySetnewList Abstraction
To prevent shallow copy
Also, Change one of the empty square into X or O SetnewItem Abstraction
To prevent shallow copy
newItem is a list that recod the sequence the squares are filled in If the computer plays X and X wins after the recursive procedure, we add the score of this square becasue it is more likely for the computer to win.
The score is added to the possibility list, and only the square where this recursive procedure start will receive the score
The score added each time is weighted by a reporter inside. If the computer wins very fast, the added score will be higher, if the computer wins until all the empty squares are filled, the square will be added a very small score. a1i1j1i1truetruetruej1true1Empty,Empty,Empty,Empty,Empty,Empty,Empty,Empty,EmptyO0X,O,X,O,X,54,486,54,OA,B,X,O,X,O,X,Empty,X,Empty,OfalsePVE0X,O,X,O,X,X,O,X,O8,7,6