Sets and Combinatorial Search Example - rohgar/scala-principles-1 GitHub Wiki

So far we have seen forms of Seq. Here we will see Sets.

Sets Sets are another basic abstraction in the Scala collections are very close to Sequences. A set is written analogously to a sequence:

val fruit = Set(”apple”, ”banana”, ”pear”)
val s = (1 to 6).toSet

Most operations on sequences are also available on sets:

s map (_ + 2)
fruit filter (_.startsWith == ”app”)
s.nonEmpty

(see Iterables Scaladoc for a list of all supported operations)

The principal differences between sets and sequences are:

1. Sets are unordered; the elements of a set do not have a predefined order in which they appear in the set
2. sets do not have duplicate elements:

s map (_ / 2) // Set(2, 0, 3, 1)

3. The fundamental operation on sets is contains:

s contains 5 // true

The eight queens problem is to place eight queens on a chessboard so that no queen is threatened by another.

• In other words, there can’t be two queens in the same row, column, or diagonal. We now develop a solution for a chessboard of any size, not just 8.
  Eg.

      0      1     2     3
   -------------------------
0  |     |  X  |     |     |
   -------------------------
1  |     |     |     |  x  |
   -------------------------
2  |  x  |     |     |     |
   -------------------------
3  |     |     |  X  |     |
   -------------------------

One way to solve the problem is to place a queen on each row. When we have placed k - 1 queens, one must place the kth queen in a column where it’s not “in check” with any other queen on the board. Eg. 0th queen doesn't matter. So if the first quen is placed as above in the (0,1) the 2nd goes in (1, 3), and so on.

We can solve this problem with a recursive algorithm:

• Suppose that we have already generated all the solutions consisting of placing k-1 queens on a board of size n.
• Each solution is represented by a list (of length k-1) containing the numbers of columns (between 0 and n-1).
• The column number of the queen in the k-1the row comes first in the list, followed by the column number of the queen in row k-2, etc.
• The solution set is thus represented as a set of lists, with one element for each solution.
• Now, to place the kth queen, we generate all possible extensions of each solution preceded by a new queen:

      0      1     2     3
   -------------------------
0  |     |  X  |     |     |
   -------------------------
1  |     |     |     |  x  |
   -------------------------
2  |  x  |     |     |     |
   -------------------------
3  |     |     |  X  |     |
   -------------------------

So using he algorithm above, the solution using the first 3 queens would be list(0, 3, 1)because we placed:

1. 3rd queen in (2, 0)
2. 2nd in (1, 3)
3. 1st in (0,1) So placing the 4th queen, our solution will be list(1, 0, 3, 1)

def queens(n: Int) = {
def placeQueens(k: Int): Set[List[Int]] = {
  if (k == 0) Set(List())
  else
  for {
    queens <- placeQueens(k - 1)
    col <- 0 until n
    if isSafe(col, queens)
    } yield col :: queens
  }
  placeQueens(n)
}

If k == 0 return empty list. Now, in the case where k is greater than 0 we have to do some real work. In general, to place k queens, we have to solve the problem of placing k - 1 queens. We'll let queens range over the set of our partial solutions returned by placeQueens(k - 1).

Next, we have to put our k queen into a certain column. We can simply try all the possible columns - col <- 0 until n. We can't place the queen in any column we please, we need to make sure it doesn't threaten any other queen. So, we'll put a filter in there, that says that the column for the queen is safe with respect to the previous queens. (isSafe(col, queens))

If it is, then we can yield a new solution, which will be our partial solution col, augmented by the queen in the new column. So it would be col :: queens.

Next we implement isSafe:

def isSafe(col: Int, queens: List[Int]): Boolean = {
  val row = queens.length
  val queensWithRow = (row - 1 to 0 by -1) zip queens
  queensWithRow forall {
    case (r, c) => col != c  && math.abs(col - c) != row - r
  }
}

It takes a column to place the new queen and an existing solution until this point, and returns a boolean indicating if it is safe to place the queen in the given column. The row assumed is the next row.

The first thing we want to do is add rows to all the queens we look at here; the row of the queen to be placed will be just queens.length, since the other queens are in rows 0 to n - 1.

Next, we want to add a row to each of our previous queens, transforming our list of Ints into a list of pairs, of row and column. We've got a set of solutions, which is something like List(0, 3, 1), with the columns of the previous queens. We want to transform that into a solution that adds the rows. The first element was actually the last row to be placed, so we'd get List((2,0), (1,3), (0,1)).

The idea here is to use a zip with a range - the range that we want to apply here is the range that goes from row - 1 to 0, by -1 steps. We zip that sequence with the list of our queens, and we call that withRow. So now we've got the partial solution of queens, represented with rows.

Now what we can do is simply check whether the ween at row and column is in check with any of our queensWithRow. forall of these queensWithRow, it must be that the new queen is not in check ...

So we take the row and the column out of the pair with a case statement, and now comes our check. What do we need to check? First, we need to make sure that the current column is not the same as any of the previous queen's columns. col != c

We also need to make sure that the queen is not in check over any of the diagonals. Meaning, the absolute difference between the two columns (math.abs(col - c)) must not be the same as the absolute difference between the two rows (row - r).

If that predicate is true, then we know that the queen is not in check over any of the diagonals with the queen in (r, c)!