Kunstig Intelligens til Brætspillet Taiji - Danmarks Tekniske Universitet

A.2 AITaijiGrowth.java 125
) ;
871 count++;
872 i n t v = min ( nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] )
, alpha , beta , 0 ) ;
873 i f ( n . a < v )
874 n . a = v ;
875 i f ( n . a > beta ) {
876 r e [ 0 ] = 0 ; // 1 = alpha beta pruning
s l a a e t t i l , 0 = s l a a e t f r a (
s l a a e t f r a da den g i v e r
problemer )
877 r e [1]= alpha ;
878 r e [2]= beta ;
879 r e [3]= n . a ;
880 r e t u r n ( r e ) ;
881 }
882 i f ( alpha < n . a )
883 alpha = n . a ;
884
885 }
886 r e t u r n ( r e ) ;
887 }
888
889 // haandtere p l a c e r i n g e n a f b r i k k e r f o r min ( ) , c h e c k e r om de
a l l e r e d e e k s i s t e r e r , haandtere alpha beta pruning
890 p r i v a t e i n t [ ] placePieceMin ( i n t [ ] [ ] b , i n t d , Node n , i n t wC,
i n t wR, i n t bC , i n t bR, i n t alpha , i n t beta ) {
891 i n t [ ] p = new i n t [ 3 ] ;
892 p = c h e c k B o a r d I n d i v i d u a l i t y ( b , d ) ;
893 i n t [ ] r e = new i n t [ 4 ] ; // r e [0]= 1 break , r e [1]= alpha , r e
[2]= beta , r e [3]= n . a
894
895 i f ( p [ 2 ] >= 0) {
896 nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] ) . par . add ( n ) ;
897 n . c h i l d r e n . add ( nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] ) ) ;
898 i n t v = max( nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] ) , alpha , beta , 1 ) ;
899 i f ( n . a > v )
900 n . a = v ;
901 i f ( n . a < alpha ) {
902 r e [ 0 ] = 0 ; // 1 = alpha beta pruning s l a a e t t i l , 0 =
s l a a e t f r a ( s l a a e t f r a da den g i v e r problemer )
903 r e [1]= alpha ;
904 r e [2]= beta ;
905 r e [3]= n . a ;
906 r e t u r n ( r e ) ;
907 }
908 i f ( beta > n . a )
909 beta = n . a ;
910 }
911 i f ( p [ 2 ] == −1){
912 p [2]= nodes [ p [ 0 ] ] [ p [ 1 ] ] . s i z e ( ) ;
913 nodes [ p [ 0 ] ] [ p [ 1 ] ] . add ( n . addChild ( tNode . createChildNode (
wC, wR, bC , bR, n ) ) ) ;
914 count++;
915 i n t v = max( nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] ) , alpha , beta , 0 ) ;