--- lib/neuralnet.c.old	2006-01-29 11:16:30.000000000 -0700
+++ lib/neuralnet.c	2006-01-29 11:21:10.000000000 -0700
@@ -386,13 +386,15 @@
 }
 extern void *NeuralNetCreateDirect( neuralnet *pnn, void *p ) {
  
-   pnn->cInput = *( ( (int *) p )++ );
-   pnn->cHidden = *( ( (int *) p )++ );
-   pnn->cOutput = *( ( (int *) p )++ );
-   pnn->nTrained = *( ( (int *) p )++ );
+   int *ip = (int *)p;
+   pnn->cInput = *( ip++ );
+   pnn->cHidden = *( ip++ );
+   pnn->cOutput = *( ip++ );
+   pnn->nTrained = *( ip++ );
    pnn->fDirect = TRUE;
-   pnn->rBetaHidden = *( ( (float *) p )++ );
-   pnn->rBetaOutput = *( ( (float *) p )++ );
+   float *fp = (float *)ip;
+   pnn->rBetaHidden = *( fp++ );
+   pnn->rBetaOutput = *( fp++ );
  
    if( pnn->cInput < 1 || pnn->cHidden < 1 || pnn->cOutput < 1 ||
      pnn->nTrained < 0 || pnn->rBetaHidden <= 0.0 ||
@@ -402,19 +404,19 @@
      return NULL;
    }
  
-   pnn->arHiddenWeight = p;
-   ( (float *) p ) += pnn->cInput * pnn->cHidden;
-   pnn->arOutputWeight = p;
-   ( (float *) p ) += pnn->cHidden * pnn->cOutput;
-   pnn->arHiddenThreshold = p;
-   ( (float *) p ) += pnn->cHidden;
-   pnn->arOutputThreshold = p;
-   ( (float *) p ) += pnn->cOutput;
+   pnn->arHiddenWeight = (void *)fp;
+   fp += pnn->cInput * pnn->cHidden;
+   pnn->arOutputWeight = (void *)fp;
+   fp += pnn->cHidden * pnn->cOutput;
+   pnn->arHiddenThreshold = (void *)fp;
+   fp += pnn->cHidden;
+   pnn->arOutputThreshold = (void *)fp;
+   fp += pnn->cOutput;
 
    pnn->savedBase = malloc( pnn->cHidden * sizeof( float ) ); 
    pnn->savedIBase = malloc( pnn->cInput * sizeof( float ) ); 
 
-   return p;
+   return (void *)fp;
 }
 
 extern int
--- eval.c.old	2006-01-29 11:24:57.000000000 -0700
+++ eval.c	2006-01-29 11:27:35.000000000 -0700
@@ -798,7 +798,9 @@
 	    if( !fstat( h, &st ) &&
 		( p = mmap( NULL, st.st_size, PROT_READ | PROT_WRITE,
 			    MAP_PRIVATE, h, 0 ) ) ) {
-		( (float *) p ) += 2; /* skip magic number and version */
+		float *fp = (float *)p;
+		fp += 2; /* skip magic number and version */
+		p = (void *)fp;
 		fReadWeights =
 		    ( p = NeuralNetCreateDirect( &nnContact, p ) ) &&
 		    ( p = NeuralNetCreateDirect( &nnRace, p ) ) &&
--- rollout.c.old	2006-01-29 11:32:54.000000000 -0700
+++ rollout.c	2006-01-29 11:32:58.000000000 -0700
@@ -219,7 +219,7 @@
     nPermutationSeed = n;
 }
 
-static int nSkip;
+static int nSkip_local;
 
 static int RolloutDice( int iTurn, int iGame, int cGames,
                             int fInitial,
@@ -234,10 +234,10 @@
 	  int j;
       
 	  if( !iGame )
-	      nSkip = 0;
+	      nSkip_local = 0;
 
-	  for( ; ; nSkip++ ) {
-	      j = aaanPermutation[ 0 ][ 0 ][ ( iGame + nSkip ) % 36 ];
+	  for( ; ; nSkip_local++ ) {
+	      j = aaanPermutation[ 0 ][ 0 ][ ( iGame + nSkip_local ) % 36 ];
 	      
 	      anDice[ 0 ] = j / 6 + 1;
 	      anDice[ 1 ] = j % 6 + 1;
@@ -265,7 +265,7 @@
 	  k; /* 36**i */
       
       for( i = 0, j = 0, k = 1; i < 6 && i <= iTurn; i++, k *= 36 )
-	  j = aaanPermutation[ i ][ iTurn ][ ( (iGame + nSkip) / k + j ) % 36 ];
+	  j = aaanPermutation[ i ][ iTurn ][ ( (iGame + nSkip_local) / k + j ) % 36 ];
       
       anDice[ 0 ] = j / 6 + 1;
       anDice[ 1 ] = j % 6 + 1;
@@ -1173,7 +1173,7 @@
       if( prc->fRotate ) 
         QuasiRandomSeed( prc->nSeed );
 
-      nSkip = prc->nSkip;
+      nSkip_local = prc->nSkip;
 
       /* ... and the RNG */
       if( prc->rngRollout != RNG_MANUAL )
@@ -1672,7 +1672,7 @@
     return -1;
 
   pes->rc.nGamesDone = cGames;
-  pes->rc.nSkip = nSkip;
+  pes->rc.nSkip = nSkip_local;
 
   return 0;