<p>There is a <code>50 x 50</code> chessboard with <strong>one</strong> knight and some pawns on it. You are given two integers <code>kx</code> and <code>ky</code> where <code>(kx, ky)</code> denotes the position of the knight, and a 2D array <code>positions</code> where <code>positions[i] = [x<sub>i</sub>, y<sub>i</sub>]</code> denotes the position of the pawns on the chessboard.</p>

<p>Alice and Bob play a <em>turn-based</em> game, where Alice goes first. In each player&#39;s turn:</p>

<ul>
	<li>The player <em>selects </em>a pawn that still exists on the board and captures it with the knight in the <strong>fewest</strong> possible <strong>moves</strong>. <strong>Note</strong> that the player can select <strong>any</strong> pawn, it <strong>might not</strong> be one that can be captured in the <strong>least</strong> number of moves.</li>
	<li><span>In the process of capturing the <em>selected</em> pawn, the knight <strong>may</strong> pass other pawns <strong>without</strong> capturing them</span>. <strong>Only</strong> the <em>selected</em> pawn can be captured in <em>this</em> turn.</li>
</ul>

<p>Alice is trying to <strong>maximize</strong> the <strong>sum</strong> of the number of moves made by <em>both</em> players until there are no more pawns on the board, whereas Bob tries to <strong>minimize</strong> them.</p>

<p>Return the <strong>maximum</strong> <em>total</em> number of moves made during the game that Alice can achieve, assuming both players play <strong>optimally</strong>.</p>

<p>Note that in one <strong>move, </strong>a chess knight has eight possible positions it can move to, as illustrated below. Each move is two cells in a cardinal direction, then one cell in an orthogonal direction.</p>

<p><img src="https://assets.leetcode.com/uploads/2024/08/01/chess_knight.jpg" style="width: 275px; height: 273px;" /></p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<div class="example-block">
<p><strong>Input:</strong> <span class="example-io">kx = 1, ky = 1, positions = [[0,0]]</span></p>

<p><strong>Output:</strong> <span class="example-io">4</span></p>

<p><strong>Explanation:</strong></p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/08/16/gif3.gif" style="width: 275px; height: 275px;" /></p>

<p>The knight takes 4 moves to reach the pawn at <code>(0, 0)</code>.</p>
</div>

<p><strong class="example">Example 2:</strong></p>

<div class="example-block">
<p><strong>Input:</strong> <span class="example-io">kx = 0, ky = 2, positions = [[1,1],[2,2],[3,3]]</span></p>

<p><strong>Output:</strong> <span class="example-io">8</span></p>

<p><strong>Explanation:</strong></p>

<p><strong><img alt="" src="https://assets.leetcode.com/uploads/2024/08/16/gif4.gif" style="width: 320px; height: 320px;" /></strong></p>

<ul>
	<li>Alice picks the pawn at <code>(2, 2)</code> and captures it in two moves: <code>(0, 2) -&gt; (1, 4) -&gt; (2, 2)</code>.</li>
	<li>Bob picks the pawn at <code>(3, 3)</code> and captures it in two moves: <code>(2, 2) -&gt; (4, 1) -&gt; (3, 3)</code>.</li>
	<li>Alice picks the pawn at <code>(1, 1)</code> and captures it in four moves: <code>(3, 3) -&gt; (4, 1) -&gt; (2, 2) -&gt; (0, 3) -&gt; (1, 1)</code>.</li>
</ul>
</div>

<p><strong class="example">Example 3:</strong></p>

<div class="example-block">
<p><strong>Input:</strong> <span class="example-io">kx = 0, ky = 0, positions = [[1,2],[2,4]]</span></p>

<p><strong>Output:</strong> <span class="example-io">3</span></p>

<p><strong>Explanation:</strong></p>

<ul>
	<li>Alice picks the pawn at <code>(2, 4)</code> and captures it in two moves: <code>(0, 0) -&gt; (1, 2) -&gt; (2, 4)</code>. Note that the pawn at <code>(1, 2)</code> is not captured.</li>
	<li>Bob picks the pawn at <code>(1, 2)</code> and captures it in one move: <code>(2, 4) -&gt; (1, 2)</code>.</li>
</ul>
</div>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li><code>0 &lt;= kx, ky &lt;= 49</code></li>
	<li><code>1 &lt;= positions.length &lt;= 15</code></li>
	<li><code>positions[i].length == 2</code></li>
	<li><code>0 &lt;= positions[i][0], positions[i][1] &lt;= 49</code></li>
	<li>All <code>positions[i]</code> are unique.</li>
	<li>The input is generated such that <code>positions[i] != [kx, ky]</code> for all <code>0 &lt;= i &lt; positions.length</code>.</li>
</ul>

class Solution:
    def maxMoves(self, kx: int, ky: int, positions: List[List[int]]) -> int:
        R, C = 50, 50

        MOVE = [(-1, -2), (-2, -1), (-2, 1), (-1, 2), (1, 2), (2, 1), (2, -1), (1, -2)]

        N = len(positions)
        tset = {(ri, ci) for ri, ci in positions}

        dp_sm = {}
        for ri, ci in positions + [(kx, ky)]:
            dp_sm[(ri, ci)] = defaultdict(int)
            dp_sm[(ri, ci)][(ri, ci)] = 0
            cnt = (ri, ci) in tset
            cur = [(ri, ci)]
            seen = set()
            seen.add((ri, ci))
            lvl = 1
            while cur and cnt != N:
                tmp = []
                for tri, tci in cur:
                    for mri, mci in MOVE:
                        nri = tri + mri
                        nci = tci + mci
                        
                        if -1 < nri < R and -1 < nci < C:
                            if (nri, nci) not in seen:
                                if (nri, nci) in tset:
                                    dp_sm[(ri, ci)][(nri, nci)] = lvl
                                    cnt += 1
                                seen.add((nri, nci))
                                tmp.append((nri, nci))
                cur = tmp
                lvl += 1

        dp = [[inf] * N for _ in range(1 << N)] # (bitmask, current_position)
        for i in range(N):
            dp[1 << i][i] = 0

        for mask in range(1 << N):
            bit_cnt = bin(mask).count('1')
            alice_turn = (N - bit_cnt) % 2 == 1

            for i in range(N):
                if dp[mask][i] in (inf, -inf):
                    if alice_turn:
                        dp[mask][i] = -inf
                    else:
                        dp[mask][i] = inf
                # to
                if (1 << i) & mask:
                    for j in range(N):
                        # from
                        if i != j and (1 << j) & mask:
                            if alice_turn: 
                                dp[mask][i] = max(dp[mask][i], dp[mask ^ (1 << i)][j] + dp_sm[tuple(positions[j])][tuple(positions[i])])
                            else:
                                dp[mask][i] = min(dp[mask][i], dp[mask ^ (1 << i)][j] + dp_sm[tuple(positions[j])][tuple(positions[i])])

        res = -inf
        for i in range(N):
            res = max(res, dp[(1 << N) - 1][i] + dp_sm[(kx, ky)][tuple(positions[i])])
        
        return res



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