Kunstig Intelligens til Brætspillet Taiji - Danmarks Tekniske Universitet

108 Bilag A
61 }
62 }
63
64 // c h e c k e r om der a l l e r e d e e r e t saadant b r a e t . Returnerer
c o r d i n a t e r n e f o r den node , h v i s der e r .
65 p r i v a t e i n t [ ] c h e c k B o a r d I n d i v i d u a l i t y ( i n t [ ] [ ] b , i n t d ) {
66 i n t [ ] p = new i n t [ 3 ] ;
67 i n t h = tModel . tHash . hashFunction3 ( b ) ;
68 p [0]= d ;
69 p [1]= h ;
70 p[2]= −1;
71 f o r ( i n t i = 0 ; i = searchD | | ! tModel . movesLeftN ( n ) ) {
83 n . a = tModel . fMap . c a l D i f ( n . nodeBoard , tModel . noCols ,
tModel . noRows ) ;
84 r e t u r n ( n . a ) ;
85 }
86 e l s e {
87 i f ( ex == 1) {
88 i f ( n . a >= beta )
89 r e t u r n ( n . a ) ;
90 }
91 n . a = −tModel . maxScore ;
92 i n t [ ] [ ] b = n . nodeBoard ;
93 i n t [ ] [ ] fb = new i n t [ tModel . noCols ] [ tModel . noRows ] ;
94 i n t d = n . d ;
95 i n t [ ] [ ] [ ] f i g s ;
96
97
98 fb = tModel . fMap . getFigBoard ( n . nodeBoard , tModel . noCols
, tModel . noRows ) ;
99 f i g s = tModel . fMap . g e t F i g s ( fb ) ;
100
101 i f ( f a l s e ) { // s a e t t e s t i l t r u e f o r at p r i n t e f i g B o a r d
og h v i l k e f i g u r e , der e r s t o e r s t med f r i e p l a d s e r
omkring s i g . T i l t e s t brug
102 System . out . p r i n t l n (” growth f i g s W: ”+ f i g s
[ 1 ] [ 0 ] [ 0 ] + ” & ”+ f i g s [ 1 ] [ 1 ] [ 0 ] + ” B: ”+ f i g s
[ 0 ] [ 0 ] [ 0 ] + ” & ”+ f i g s [ 0 ] [ 1 ] [ 0 ] ) ;
103 printFB ( fb ) ;
104 }
105
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