Kunstig Intelligens til Brætspillet Taiji - Danmarks Tekniske Universitet

136 Bilag A
291 }
292
293 // Min−funktionen , l a v e t t i l holde s i g inden f o r e t 4x4 a r e a l
paa b r a e t t e t
294 p r i v a t e i n t min ( Node n , i n t alpha , i n t beta , i n t ex ) {
295 i f ( n . d >= searchD | | ! tModel . movesLeftN ( n ) ) {
296 n . a = tModel . fMap . c a l D i f ( n . nodeBoard , tModel . noCols ,
tModel . noRows ) ;
297 r e t u r n ( n . a ) ;
298 }
299 e l s e {
300 n . a = tModel . maxScore ;
301 i n t [ ] [ ] b = n . nodeBoard ;
302 i n t d = n . d ;
303 // boolean Break = f a l s e ;
304 f o r ( i n t c=c o l S t a r t ; c v )
316 n . a = v ;
317 i f ( n . a < alpha ) {
318 b [ c ] [ r ] = 2 ;
319 b [ c ] [ r +1] = 2 ;
320 r e t u r n ( n . a ) ;
321 }
322 i f ( beta > n . a )
323 beta = n . a ;
324 }
325 i f ( p [ 2 ] == −1){
326 p [2]= nodes [ p [ 0 ] ] [ p [ 1 ] ] . s i z e ( ) ;
327 nodes [ p [ 0 ] ] [ p [ 1 ] ] . add ( n . addChild ( tNode .
createChildNode ( c , r , c , r +1, n ) ) ) ;
328 count++;
329 i n t v = max( nodes [ p [ 0 ] ] [ p [ 1 ] ] . get ( p [ 2 ] )
, alpha , beta , 0 ) ;
330 i f ( n . a > v )
331 n . a = v ;
332 i f ( n . a < alpha ) {
333 b [ c ] [ r ] = 2 ;
334 b [ c ] [ r +1] = 2 ;
335 r e t u r n ( n . a ) ;
336 }
337 i f ( beta > n . a )
338 beta = n . a ;
339 }