feat(ncs-110): feed NNUE root-move scores into search move ordering (#83)

Pre-evaluated NNUE scores from NNUEBot.batchEvaluateRoot are now passed
as root hints into AlphaBetaSearch, improving move ordering at ply 0 before
the TT is populated. Hints are threaded immutably through SearchParams to
satisfy the no-var constraint.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Janis Eccarius <eccariusjanis@gmail.com>
Reviewed-on: #83

modules/official-bots/src/main/scala/de/nowchess/bot/bots/NNUEBot.scala

@@ -28,7 +28,7 @@ object NNUEBot:
           else
             val scored   = batchEvaluateRoot(rules, context, moves)
             val bestMove = scored.maxBy(_._2)._1
-            search.bestMoveWithTime(context, allocateTime(scored), blockedMoves).orElse(Some(bestMove))
+            search.bestMoveWithTime(context, allocateTime(scored), blockedMoves, scored.toMap).orElse(Some(bestMove))
         }
 
   private def batchEvaluateRoot(rules: RuleSet, context: GameContext, moves: List[Move]): List[(Move, Int)] =

modules/official-bots/src/main/scala/de/nowchess/bot/logic/AlphaBetaSearch.scala

@@ -32,6 +32,8 @@ final class AlphaBetaSearch(
   private val nodeCount   = AtomicInteger(0)
   private val ordering    = MoveOrdering.OrderingContext()
 
+  def lastNodeCount: Int = nodeCount.get()
+
   private final case class QuiescenceNode(
       context: GameContext,
       ply: Int,
@@ -47,6 +49,17 @@ final class AlphaBetaSearch(
     bestMove(context, maxDepth, Set.empty)
 
   def bestMove(context: GameContext, maxDepth: Int, excludedRootMoves: Set[Move]): Option[Move] =
+    doDepthSearch(context, maxDepth, excludedRootMoves, Map.empty)
+
+  def bestMove(context: GameContext, maxDepth: Int, excludedRootMoves: Set[Move], hints: Map[Move, Int]): Option[Move] =
+    doDepthSearch(context, maxDepth, excludedRootMoves, hints)
+
+  private def doDepthSearch(
+      context: GameContext,
+      maxDepth: Int,
+      excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
+  ): Option[Move] =
     tt.clear()
     ordering.clear()
     weights.initAccumulator(context)
@@ -66,6 +79,7 @@ final class AlphaBetaSearch(
           ASPIRATION_DELTA,
           rootHash,
           excludedRootMoves,
+          hints,
         )
         (move.orElse(bestSoFar), score)
       }
@@ -78,6 +92,22 @@ final class AlphaBetaSearch(
     bestMoveWithTime(context, timeBudgetMs, Set.empty)
 
   def bestMoveWithTime(context: GameContext, timeBudgetMs: Long, excludedRootMoves: Set[Move]): Option[Move] =
+    doTimedSearch(context, timeBudgetMs, excludedRootMoves, Map.empty)
+
+  def bestMoveWithTime(
+      context: GameContext,
+      timeBudgetMs: Long,
+      excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
+  ): Option[Move] =
+    doTimedSearch(context, timeBudgetMs, excludedRootMoves, hints)
+
+  private def doTimedSearch(
+      context: GameContext,
+      timeBudgetMs: Long,
+      excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
+  ): Option[Move] =
     tt.clear()
     ordering.clear()
     weights.initAccumulator(context)
@@ -100,6 +130,7 @@ final class AlphaBetaSearch(
           ASPIRATION_DELTA,
           rootHash,
           excludedRootMoves,
+          hints,
         )
         loop(move.orElse(bestSoFar), score, depth + 1, depth)
 
@@ -124,14 +155,17 @@ final class AlphaBetaSearch(
       initialWindow: Int,
       rootHash: Long,
       excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
   ): (Int, Option[Move]) =
     val state = SearchState(rootHash, Map(rootHash -> 1))
 
     @scala.annotation.tailrec
     def loop(currentAlpha: Int, currentBeta: Int, delta: Int, attempt: Int): (Int, Option[Move]) =
-      if attempt >= 3 || attempt >= depth then search(context, depth, 0, Window(-INF, INF), state, excludedRootMoves)
+      if attempt >= 3 || attempt >= depth then
+        search(context, depth, 0, Window(-INF, INF), state, excludedRootMoves, hints)
       else
-        val (score, move) = search(context, depth, 0, Window(currentAlpha, currentBeta), state, excludedRootMoves)
+        val (score, move) =
+          search(context, depth, 0, Window(currentAlpha, currentBeta), state, excludedRootMoves, hints)
         if score > currentAlpha && score < currentBeta then (score, move)
         else if score <= currentAlpha then
           loop(score - delta, currentBeta, math.min(delta * 2, ASPIRATION_DELTA_MAX), attempt + 1)
@@ -156,12 +190,14 @@ final class AlphaBetaSearch(
       beta: Int,
       state: SearchState,
       excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
   ): Option[Int] =
     val nullCtx        = nullMoveContext(context)
     val nullState      = state.advance(ZobristHash.hash(nullCtx))
     val reductionDepth = math.max(0, depth - 1 - NULL_MOVE_R)
     weights.copyAccumulator(ply, ply + 1)
-    val (score, _) = search(nullCtx, reductionDepth, ply + 1, Window(-beta, -beta + 1), nullState, excludedRootMoves)
+    val (score, _) =
+      search(nullCtx, reductionDepth, ply + 1, Window(-beta, -beta + 1), nullState, excludedRootMoves, hints)
     if -score >= beta then Some(beta) else None
 
   /** Negamax alpha-beta search returning (score, best move). */
@@ -172,8 +208,9 @@ final class AlphaBetaSearch(
       window: Window,
       state: SearchState,
       excludedRootMoves: Set[Move],
+      hints: Map[Move, Int],
   ): (Int, Option[Move]) =
-    val params = SearchParams(context, depth, ply, window, state, excludedRootMoves)
+    val params = SearchParams(context, depth, ply, window, state, excludedRootMoves, hints)
     searchNode(params)
 
   private def searchNode(params: SearchParams): (Int, Option[Move]) =
@@ -235,13 +272,14 @@ final class AlphaBetaSearch(
             params.window.beta,
             params.state,
             params.excludedRootMoves,
+            params.rootHints,
           ),
         )
         .flatten
 
     nullResult.map((_, None)).getOrElse {
       val ttBest  = tt.probe(params.state.hash).flatMap(_.bestMove)
-      val ordered = MoveOrdering.sort(params.context, legalMoves, ttBest, params.ply, ordering)
+      val ordered = MoveOrdering.sort(params.context, legalMoves, ttBest, params.ply, ordering, params.rootHints)
       searchSequential(
         params.context,
         params.depth,
@@ -250,6 +288,7 @@ final class AlphaBetaSearch(
         ordered,
         params.state,
         params.excludedRootMoves,
+        params.rootHints,
       )
     }
 
@@ -280,6 +319,7 @@ final class AlphaBetaSearch(
         Window(-a - 1, -a),
         childState,
         params.excludedRootMoves,
+        params.rootHints,
       )
       val s = -rs
       if s > a then
@@ -290,6 +330,7 @@ final class AlphaBetaSearch(
           Window(betaNeg, -a),
           childState,
           params.excludedRootMoves,
+          params.rootHints,
         )
         -fs
       else s
@@ -301,6 +342,7 @@ final class AlphaBetaSearch(
         Window(betaNeg, -a),
         childState,
         params.excludedRootMoves,
+        params.rootHints,
       )
       -rs
 
@@ -364,8 +406,9 @@ final class AlphaBetaSearch(
       ordered: List[Move],
       state: SearchState,
       excludedRootMoves: Set[Move],
+      rootHints: Map[Move, Int] = Map.empty,
   ): (Int, Option[Move]) =
-    val params                        = SearchParams(context, depth, ply, window, state, excludedRootMoves)
+    val params                        = SearchParams(context, depth, ply, window, state, excludedRootMoves, rootHints)
     val (bestMove, bestScore, cutoff) = searchLoop(0, 0, LoopAcc(None, -INF, window.alpha), params, ordered)
     val flag =
       if cutoff then TTFlag.Lower

modules/official-bots/src/main/scala/de/nowchess/bot/logic/MoveOrdering.scala

@@ -38,8 +38,10 @@ object MoveOrdering:
       ttBestMove: Option[Move],
       ply: Int = 0,
       ordering: OrderingContext = new OrderingContext(),
+      rootHints: Map[Move, Int] = Map.empty,
   ): Int =
     if ttBestMove.exists(m => m.from == move.from && m.to == move.to) then Int.MaxValue
+    else if ply == 0 && rootHints.nonEmpty then rootHints.getOrElse(move, Int.MinValue / 2)
     else
       move.moveType match
         case MoveType.Promotion(PromotionPiece.Queen) =>
@@ -56,8 +58,9 @@ object MoveOrdering:
       ttBestMove: Option[Move],
       ply: Int = 0,
       ordering: OrderingContext = new OrderingContext(),
+      rootHints: Map[Move, Int] = Map.empty,
   ): List[Move] =
-    moves.sortBy(m => -score(context, m, ttBestMove, ply, ordering))
+    moves.sortBy(m => -score(context, m, ttBestMove, ply, ordering, rootHints))
 
   private def scoreQuietMove(move: Move, ply: Int, ordering: OrderingContext): Int =
     val isKiller = ordering.getKillerMoves(ply).exists(k => k.from == move.from && k.to == move.to)

modules/official-bots/src/main/scala/de/nowchess/bot/logic/TranspositionTable.scala

@@ -14,6 +14,7 @@ final case class SearchParams(
     window: Window,
     state: SearchState,
     excludedRootMoves: Set[Move],
+    rootHints: Map[Move, Int] = Map.empty,
 )
 
 final case class SearchState(hash: Long, repetitions: Map[Long, Int]):

modules/official-bots/src/test/scala/de/nowchess/bot/AlphaBetaSearchTest.scala

@@ -312,6 +312,24 @@ class AlphaBetaSearchTest extends AnyFunSuite with Matchers:
     val search = AlphaBetaSearch(qRules, weights = ZeroEval)
     search.bestMove(GameContext.initial, maxDepth = 1) should be(Some(rootMove))
 
+  test("bestMove with root hints returns a valid move without regression"):
+    val context    = GameContext.initial
+    val legalMoves = DefaultRules.allLegalMoves(context)
+    val hints      = legalMoves.zipWithIndex.map { case (m, i) => m -> (legalMoves.length - i) }.toMap
+    val withHints = AlphaBetaSearch(DefaultRules, weights = EvaluationClassic)
+      .bestMove(context, maxDepth = 2, Set.empty, hints)
+    withHints should not be None
+    legalMoves should contain(withHints.get)
+
+  test("bestMoveWithTime with root hints returns a valid move without regression"):
+    val context    = GameContext.initial
+    val legalMoves = DefaultRules.allLegalMoves(context)
+    val hints      = legalMoves.zipWithIndex.map { case (m, i) => m -> (legalMoves.length - i) }.toMap
+    val withHints = AlphaBetaSearch(DefaultRules, weights = EvaluationClassic)
+      .bestMoveWithTime(context, 500L, Set.empty, hints)
+    withHints should not be None
+    legalMoves should contain(withHints.get)
+
   test("quiescence depth-limit in-check branch is exercised"):
     val rootMove            = Move(Square(File.E, Rank.R2), Square(File.E, Rank.R3), MoveType.Normal())
     val capMove             = Move(Square(File.D, Rank.R2), Square(File.D, Rank.R3), MoveType.Normal(true))

modules/official-bots/src/test/scala/de/nowchess/bot/MoveOrderingTest.scala

@@ -217,3 +217,60 @@ class MoveOrderingTest extends AnyFunSuite with Matchers:
     val castle  = Move(Square(File.E, Rank.R1), Square(File.G, Rank.R1), MoveType.CastleKingside)
 
     MoveOrdering.score(context, castle, None) should be(0)
+
+  test("root hints override capture heuristics at ply 0"):
+    val board = Board(
+      Map(
+        Square(File.E, Rank.R4) -> Piece.WhiteQueen,
+        Square(File.E, Rank.R5) -> Piece.BlackPawn,
+        Square(File.D, Rank.R5) -> Piece.BlackRook,
+      ),
+    )
+    val context     = GameContext.initial.withBoard(board).withTurn(Color.White)
+    val quietMove   = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R6))
+    val rookCapture = Move(Square(File.E, Rank.R4), Square(File.D, Rank.R5), MoveType.Normal(true))
+    val hints       = Map(quietMove -> 500, rookCapture -> 100)
+
+    MoveOrdering.score(context, quietMove, None, ply = 0, rootHints = hints) should equal(500)
+    MoveOrdering.score(context, rookCapture, None, ply = 0, rootHints = hints) should equal(100)
+    MoveOrdering.score(context, rookCapture, None, ply = 0, rootHints = hints) should be <
+      MoveOrdering.score(context, quietMove, None, ply = 0, rootHints = hints)
+
+  test("root hints ignored at ply > 0"):
+    val board   = Board(Map(Square(File.E, Rank.R4) -> Piece.WhiteQueen, Square(File.E, Rank.R5) -> Piece.BlackPawn))
+    val context = GameContext.initial.withBoard(board).withTurn(Color.White)
+    val capture = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R5), MoveType.Normal(true))
+    val quiet   = Move(Square(File.E, Rank.R4), Square(File.D, Rank.R4))
+    val hints   = Map(quiet -> 99999, capture -> -99999)
+
+    val captureScore = MoveOrdering.score(context, capture, None, ply = 1, rootHints = hints)
+    val quietScore   = MoveOrdering.score(context, quiet, None, ply = 1, rootHints = hints)
+    captureScore should be > quietScore
+
+  test("move absent from root hints gets Int.MinValue / 2 fallback"):
+    val board   = Board(Map(Square(File.E, Rank.R4) -> Piece.WhiteQueen))
+    val context = GameContext.initial.withBoard(board).withTurn(Color.White)
+    val move1   = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R6))
+    val move2   = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R5))
+    val hints   = Map(move1 -> 0)
+
+    MoveOrdering.score(context, move2, None, ply = 0, rootHints = hints) should equal(Int.MinValue / 2)
+
+  test("sort uses root hints at ply 0 to reorder moves"):
+    val board = Board(
+      Map(
+        Square(File.E, Rank.R4) -> Piece.WhiteQueen,
+        Square(File.E, Rank.R5) -> Piece.BlackPawn,
+        Square(File.D, Rank.R5) -> Piece.BlackRook,
+      ),
+    )
+    val context     = GameContext.initial.withBoard(board).withTurn(Color.White)
+    val rookCapture = Move(Square(File.E, Rank.R4), Square(File.D, Rank.R5), MoveType.Normal(true))
+    val pawnCapture = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R5), MoveType.Normal(true))
+    val quiet       = Move(Square(File.E, Rank.R4), Square(File.E, Rank.R6))
+    val hints       = Map(quiet -> 9999, pawnCapture -> 500, rookCapture -> 100)
+
+    val sorted = MoveOrdering.sort(context, List(rookCapture, pawnCapture, quiet), None, ply = 0, rootHints = hints)
+    sorted.head should equal(quiet)
+    sorted(1) should equal(pawnCapture)
+    sorted(2) should equal(rookCapture)