Fix weight interpolation thanks to cyrri

code/botlib/be_ai_weight.c

@@ -593,9 +593,12 @@ float FuzzyWeight_r(int *inventory, fuzzyseperator_t *fs)
 			if (fs->next->child) w2 = FuzzyWeight_r(inventory, fs->next->child);
 			else w2 = fs->next->weight;
 			//the scale factor
-			scale = (float) (inventory[fs->index] - fs->value) / (fs->next->value - fs->value);
+			if(fs->next->value == MAX_INVENTORYVALUE) // is fs->next the default case?
+        		return w2;      // can't interpolate, return default weight
+			else
+				scale = (float) (inventory[fs->index] - fs->value) / (fs->next->value - fs->value);
 			//scale between the two weights
-			return scale * w1 + (1 - scale) * w2;
+			return (1 - scale) * w1 + scale * w2;
 		} //end if
 		return FuzzyWeight_r(inventory, fs->next);
 	} //end else if
@@ -627,9 +630,12 @@ float FuzzyWeightUndecided_r(int *inventory, fuzzyseperator_t *fs)
 			if (fs->next->child) w2 = FuzzyWeight_r(inventory, fs->next->child);
 			else w2 = fs->next->minweight + random() * (fs->next->maxweight - fs->next->minweight);
 			//the scale factor
-			scale = (float) (inventory[fs->index] - fs->value) / (fs->next->value - fs->value);
+			if(fs->next->value == MAX_INVENTORYVALUE) // is fs->next the default case?
+        		return w2;      // can't interpolate, return default weight
+			else
+				scale = (float) (inventory[fs->index] - fs->value) / (fs->next->value - fs->value);
 			//scale between the two weights
-			return scale * w1 + (1 - scale) * w2;
+			return (1 - scale) * w1 + scale * w2;
 		} //end if
 		return FuzzyWeightUndecided_r(inventory, fs->next);
 	} //end else if