{- Copyright (C) 2018 Dr. Alistair Ward This file is part of BishBosh. BishBosh is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. BishBosh is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with BishBosh. If not, see . -} {- | [@AUTHOR@] Dr. Alistair Ward [@DESCRIPTION@] * Performs an search, implemented using . * Moves are dynamically re-ordering using the killer-heuristic. * & s are detected. -} module BishBosh.Search.AlphaBeta( -- * Types -- ** Type-synonyms -- Transformation, -- ** Data-types -- Result(), -- * Functions extractSelectedTurns, -- updateKillerMoves, -- findTranspositionTerminalQuantifiedGame, -- updateTranspositions, negaMax, -- negateFitnessOfResult, -- addNPositionsToResult ) where import BishBosh.Evaluation.QuantifiedGame((<=>), (===)) import Control.Applicative((<|>)) import Control.Arrow((&&&)) import qualified BishBosh.Component.QualifiedMove as Component.QualifiedMove import qualified BishBosh.Component.Turn as Component.Turn import qualified BishBosh.Data.Exception as Data.Exception import qualified BishBosh.Evaluation.PositionHashQuantifiedGameTree as Evaluation.PositionHashQuantifiedGameTree import qualified BishBosh.Evaluation.QuantifiedGame as Evaluation.QuantifiedGame import qualified BishBosh.Input.SearchOptions as Input.SearchOptions import qualified BishBosh.Model.Game as Model.Game import qualified BishBosh.Notation.MoveNotation as Notation.MoveNotation import qualified BishBosh.Property.Arboreal as Property.Arboreal import qualified BishBosh.Search.DynamicMoveData as Search.DynamicMoveData import qualified BishBosh.Search.KillerMoves as Search.KillerMoves import qualified BishBosh.Search.SearchState as Search.SearchState import qualified BishBosh.Search.Transpositions as Search.Transpositions import qualified BishBosh.Search.TranspositionValue as Search.TranspositionValue import qualified BishBosh.State.InstancesByPosition as State.InstancesByPosition import qualified BishBosh.State.TurnsByLogicalColour as State.TurnsByLogicalColour import qualified BishBosh.Type.Count as Type.Count import qualified BishBosh.Type.Crypto as Type.Crypto import qualified Control.Exception import qualified Control.Monad.Reader import qualified Data.Default import qualified Data.Maybe import qualified Data.Tree -- | The type returned by 'negaMax'. data Result positionHash = MkResult { getDynamicMoveData :: Search.DynamicMoveData.DynamicMoveData positionHash, -- ^ Killer moves & Transpositions. getQuantifiedGame :: Evaluation.QuantifiedGame.QuantifiedGame, getNPositionsEvaluated :: Type.Count.NPositions -- ^ The total number of nodes analysed, before making the selection. } {- | * Drop the specified number of plies; typically those made before starting the search. * CAVEAT: abandons the fitness component of the quantified game. -} extractSelectedTurns :: Type.Count.NPlies -> Result positionHash -> (Search.DynamicMoveData.DynamicMoveData positionHash, [Component.Turn.Turn], Type.Count.NPositions) extractSelectedTurns nPlies MkResult { getDynamicMoveData = dynamicMoveData, getQuantifiedGame = quantifiedGame, getNPositionsEvaluated = nPositionsEvaluated } = ( dynamicMoveData, Evaluation.QuantifiedGame.getLatestTurns nPlies quantifiedGame, nPositionsEvaluated ) -- | Record the last move as a killer, unless it's a capture move. updateKillerMoves :: Model.Game.Game -> Search.DynamicMoveData.Transformation positionHash updateKillerMoves game | Just lastTurn <- Model.Game.maybeLastTurn game = if Component.Turn.isCapture lastTurn then id -- This move was (assuming appropriate Search-options) statically sorted. else Search.DynamicMoveData.updateKillerMoves . Search.KillerMoves.insert ( State.TurnsByLogicalColour.getNPlies $ Model.Game.getTurnsByLogicalColour game ) $ Search.DynamicMoveData.mkKillerMoveKeyFromTurn lastTurn | otherwise = Control.Exception.throw . Data.Exception.mkNullDatum . showString "BishBosh.Search.AlphaBeta.updateKillerMoves:\tzero turns have been made; " $ shows game "." {- | * Track the specified move-sequence down the /positionHashQuantifiedGameTree/ & retrieve the fitness from the terminal quantified game. * CAVEAT: the return-value, is quantified from the perspective of the player who is about to move. -} findTranspositionTerminalQuantifiedGame :: Evaluation.PositionHashQuantifiedGameTree.PositionHashQuantifiedGameTree positionHash -> Search.TranspositionValue.TranspositionValue Component.QualifiedMove.QualifiedMove -> Evaluation.QuantifiedGame.QuantifiedGame findTranspositionTerminalQuantifiedGame positionHashQuantifiedGameTree transpositionValue = Data.Maybe.maybe ( Control.Exception.throw . Data.Exception.mkSearchFailure . showString "BishBosh.Search.AlphaBeta.findTranspositionTerminalQuantifiedGame:\tEvaluation.PositionHashQuantifiedGameTree.traceMatchingMoveSequence failed; " . shows transpositionValue . showString ":\n" $ ( Notation.MoveNotation.showsNotationFloatToNDecimals Data.Default.def {-move-notation-} 3 {-decimal digits-} $ Property.Arboreal.prune (fromIntegral inferredSearchDepth) positionHashQuantifiedGameTree ) "" ) ( ( if even inferredSearchDepth then Evaluation.QuantifiedGame.negateFitness -- The opponent made the last move in the list, & therefore defined the fitness. else id ) . Evaluation.PositionHashQuantifiedGameTree.getQuantifiedGame . last ) . Evaluation.PositionHashQuantifiedGameTree.traceMatchingMoveSequence positionHashQuantifiedGameTree $ Search.TranspositionValue.getQualifiedMoves transpositionValue where inferredSearchDepth = Search.TranspositionValue.inferSearchDepth transpositionValue -- | Record a qualifiedMove-sequence in the transposition-table. updateTranspositions :: Ord positionHash => Search.TranspositionValue.IsOptimal -> Type.Count.NPlies -> positionHash -> [Component.Turn.Turn] -> Evaluation.PositionHashQuantifiedGameTree.PositionHashQuantifiedGameTree positionHash -> Search.DynamicMoveData.Transformation positionHash updateTranspositions isOptimal nPlies positionHash turns positionHashQuantifiedGameTree = Search.DynamicMoveData.updateTranspositions . Search.Transpositions.insert ( Evaluation.QuantifiedGame.getFitness . findTranspositionTerminalQuantifiedGame positionHashQuantifiedGameTree ) positionHash {-the hash of the game before the first move in the sequence-} . Search.TranspositionValue.mkTranspositionValue isOptimal nPlies $ map Component.Turn.getQualifiedMove turns {- | * Implements a depth-first search (implemented as nega-max), with alpha-beta pruning. * /alpha/ is the minimum fitness of which the maximising player is assured. * /beta/ is the maximum fitness which the minimising player will tolerate. -} negaMax :: Ord positionHash => Type.Count.NPlies -- ^ The depth to which the tree should be searched; i.e. the number of plies to look-ahead. -> Search.SearchState.SearchState positionHash -> Input.SearchOptions.Reader (Result positionHash) {-# SPECIALISE negaMax :: Type.Count.NPlies -> Search.SearchState.SearchState Type.Crypto.PositionHash -> Input.SearchOptions.Reader (Result Type.Crypto.PositionHash) #-} negaMax initialSearchDepth initialSearchState = do maybeMinimumTranspositionSearchDepth <- Control.Monad.Reader.asks Input.SearchOptions.maybeMinimumTranspositionSearchDepth recordKillerMoves <- Control.Monad.Reader.asks Input.SearchOptions.recordKillerMoves trapRepeatedPositions <- Control.Monad.Reader.asks Input.SearchOptions.getTrapRepeatedPositions let getNPlies = State.TurnsByLogicalColour.getNPlies . Model.Game.getTurnsByLogicalColour -- Abbreviate. descend :: Ord positionHash => Evaluation.QuantifiedGame.OpenInterval -> Type.Count.NPlies -> Search.SearchState.SearchState positionHash -> Result positionHash descend (maybeAlphaQuantifiedGame, maybeBetaQuantifiedGame) searchDepth searchState | searchDepth == 0 || Model.Game.isTerminated game = MkResult { getDynamicMoveData = dynamicMoveData, getQuantifiedGame = Evaluation.QuantifiedGame.negateFitness quantifiedGame, -- CAVEAT: zero new moves have been applied, so the last move was the opponent's. getNPositionsEvaluated = 1 -- Fitness-negation requires evaluation. } -- Terminate the recursion. | useTranspositions , Just transpositionValue <- Search.Transpositions.find positionHash $ Search.DynamicMoveData.getTranspositions dynamicMoveData -- Look for a previously encountered position with a matching positionHash. , let -- selectMaxUsingTranspositions :: Result positionHash selectMaxUsingTranspositions = selectMaxWithSorter $ Data.Maybe.fromMaybe ( Control.Exception.throw . Data.Exception.mkSearchFailure . showString "BishBosh.Search.AlphaBeta.negaMax.descend:\tEvaluation.PositionHashQuantifiedGameTree.promoteMatchingMoveSequence failed; " $ shows transpositionValue "." -- N.B.: perhaps because of hash-collision. ) . Evaluation.PositionHashQuantifiedGameTree.promoteMatchingMoveSequence ( Search.TranspositionValue.getQualifiedMoves transpositionValue ) -- For efficiency, promote moves in the positionHashQuantifiedGameTree, using the knowledge in the transposition. = if Search.TranspositionValue.inferSearchDepth transpositionValue < searchDepth then selectMaxUsingTranspositions -- This transposition resulted from a search-depth which is insufficient to compose a valid response to this search. else let transposedQuantifiedGame = findTranspositionTerminalQuantifiedGame positionHashQuantifiedGameTree transpositionValue in if Search.TranspositionValue.getIsOptimal transpositionValue then MkResult { getDynamicMoveData = dynamicMoveData, getQuantifiedGame = Control.Exception.assert (transposedQuantifiedGame == getQuantifiedGame selectMaxUsingTranspositions) transposedQuantifiedGame, getNPositionsEvaluated = 0 } else Data.Maybe.maybe selectMaxUsingTranspositions ( \betaQuantifiedGame -> if uncurry (<) $ (($ transposedQuantifiedGame) &&& ($ betaQuantifiedGame)) Evaluation.QuantifiedGame.getFitness then selectMaxUsingTranspositions else MkResult { getDynamicMoveData = dynamicMoveData, getQuantifiedGame = Control.Exception.assert (betaQuantifiedGame == getQuantifiedGame selectMaxUsingTranspositions) betaQuantifiedGame, getNPositionsEvaluated = 0 } -- Beta-cutoff. ) maybeBetaQuantifiedGame | otherwise = selectMaxWithSorter id where (positionHashQuantifiedGameTree, dynamicMoveData) = Search.SearchState.getPositionHashQuantifiedGameTree &&& Search.SearchState.getDynamicMoveData $ searchState useTranspositions = Data.Maybe.maybe False (searchDepth >=) maybeMinimumTranspositionSearchDepth (positionHash, quantifiedGame) = Evaluation.PositionHashQuantifiedGameTree.getRootPositionHash &&& Evaluation.PositionHashQuantifiedGameTree.getRootQuantifiedGame $ positionHashQuantifiedGameTree game = Evaluation.QuantifiedGame.getGame quantifiedGame -- Prior to application of any move from the forest. (nPlies, nDistinctPositions) = getNPlies &&& State.InstancesByPosition.getNDistinctPositions . Model.Game.getInstancesByPosition $ game -- Count the distinct positions since the last irreversible move. -- selectMaxWithSorter :: (Evaluation.PositionHashQuantifiedGameTree.Forest positionHash -> Evaluation.PositionHashQuantifiedGameTree.Forest positionHash) -> Result positionHash selectMaxWithSorter forestSorter = selectMax dynamicMoveData maybeAlphaQuantifiedGame . forestSorter . ( if recordKillerMoves then Evaluation.PositionHashQuantifiedGameTree.sortNonCaptureMoves ( Search.KillerMoves.sortByHistoryHeuristic ( Model.Game.getNextLogicalColour game ) ( Search.DynamicMoveData.mkKillerMoveKeyFromTurn . Evaluation.QuantifiedGame.getLastTurn . Evaluation.PositionHashQuantifiedGameTree.getRootQuantifiedGame' ) $ Search.DynamicMoveData.getKillerMoves dynamicMoveData ) -- Dynamically advance the evaluation of killer-moves, to just after the statically sorted capture-moves. else id ) . Data.Tree.subForest $ Evaluation.PositionHashQuantifiedGameTree.deconstruct positionHashQuantifiedGameTree -- selectMax :: Search.DynamicMoveData.DynamicMoveData positionHash -> Maybe Evaluation.QuantifiedGame.QuantifiedGame -> Evaluation.PositionHashQuantifiedGameTree.Forest positionHash -> Result positionHash selectMax dynamicMoveData' maybeAlphaQuantifiedGame' (node : remainingNodes) | trapRepeatedPositions , nDistinctPositions >= fromIntegral State.InstancesByPosition.leastCyclicPlies -- CAVEAT: accounting for the typically (except the initial position) unrepeatable first distinct position. , State.InstancesByPosition.getNDistinctPositions ( Model.Game.getInstancesByPosition . Evaluation.QuantifiedGame.getGame $ Evaluation.PositionHashQuantifiedGameTree.getRootQuantifiedGame' node -- If the size hasn't increased, then the recently added position must have already been a member; (size == 1) during successive unrepeatable moves also, but that exception is caught above. ) == nDistinctPositions = selectMax dynamicMoveData' ( maybeAlphaQuantifiedGame' <|> Just quantifiedGame'' -- CAVEAT: guard against exhausting all nodes without defining alpha. ) remainingNodes -- Skip this repetitive node & recurse through the remaining nodes at this depth. | Just betaQuantifiedGame <- maybeBetaQuantifiedGame -- Beta-cutoff can't occur until beta has been defined. , let fitnessComparedWithBeta = quantifiedGame'' <=> betaQuantifiedGame , fitnessComparedWithBeta /= LT = result'' { getDynamicMoveData = ( if recordKillerMoves && not ( fitnessComparedWithBeta == EQ && quantifiedGame'' === betaQuantifiedGame -- betaQuantifiedGame was copied in the terminal case of 'selectMax', from one of the open-interval's boundaries. ) -- Confirm that betaQuantifiedGame is beneath the current node. then updateKillerMoves $ Evaluation.QuantifiedGame.getGame quantifiedGame'' else id ) dynamicMoveData'', getQuantifiedGame = betaQuantifiedGame } -- Beta-cutoff; the solution-space is either zero or negative. | otherwise = let isFitter = Data.Maybe.maybe True {-alpha is undefined => anything qualifies-} ( \alphaQuantifiedGame -> uncurry (>) $ (($ quantifiedGame'') &&& ($ alphaQuantifiedGame)) Evaluation.QuantifiedGame.getFitness ) maybeAlphaQuantifiedGame' in addNPositionsToResult ( getNPositionsEvaluated result'' ) $ selectMax ( ( if useTranspositions && isFitter then updateTranspositions False {-isOptimal-} nPlies positionHash {-the hash of the game before the first move in the sequence-} ( Evaluation.QuantifiedGame.getLatestTurns nPlies quantifiedGame'' -- Discard turns previously applied to the game to which the positionHash refers. ) positionHashQuantifiedGameTree else id ) dynamicMoveData'' ) ( if isFitter then Just quantifiedGame'' -- Increase the alpha solution (i.e. the lower acceptable solution-bound). else maybeAlphaQuantifiedGame' ) remainingNodes -- Recurse through the remaining moves at this depth. where result''@MkResult { getDynamicMoveData = dynamicMoveData'', getQuantifiedGame = quantifiedGame'' } = negateFitnessOfResult . descend ( curry Evaluation.QuantifiedGame.negateInterval maybeAlphaQuantifiedGame' maybeBetaQuantifiedGame ) ( pred searchDepth ) $ Search.SearchState.mkSearchState ( Evaluation.PositionHashQuantifiedGameTree.fromBarePositionHashQuantifiedGameTree node ) dynamicMoveData' -- Recurse. selectMax dynamicMoveData' maybeAlphaQuantifiedGame' [] = MkResult { getDynamicMoveData = dynamicMoveData', getQuantifiedGame = Data.Maybe.fromMaybe ( Data.Maybe.fromMaybe ( Control.Exception.throw . Data.Exception.mkResultUndefined . showString "BishBosh.Search.AlphaBeta.negaMax.descend.selectMax:\tthere are zero nodes to process, but neither alpha nor beta is defined; " $ shows game "." ) maybeBetaQuantifiedGame -- Return the only viable position known. ) maybeAlphaQuantifiedGame', -- Return the fittest viable position found. getNPositionsEvaluated = 0 } -- Zero moves remain => terminate the recursion. return {-to Reader-monad-} . ( \result@MkResult { getDynamicMoveData = dynamicMoveData, getQuantifiedGame = quantifiedGame } -> let positionHashQuantifiedGameTree = Search.SearchState.getPositionHashQuantifiedGameTree initialSearchState nPlies = getNPlies . Evaluation.QuantifiedGame.getGame $ Evaluation.PositionHashQuantifiedGameTree.getRootQuantifiedGame positionHashQuantifiedGameTree in result { getDynamicMoveData = updateTranspositions True {-Optimal-} nPlies ( Evaluation.PositionHashQuantifiedGameTree.getRootPositionHash positionHashQuantifiedGameTree ) ( Evaluation.QuantifiedGame.getLatestTurns nPlies quantifiedGame ) positionHashQuantifiedGameTree dynamicMoveData } ) $ descend Evaluation.QuantifiedGame.unboundedInterval initialSearchDepth initialSearchState -- | The type of a function which transforms the result. type Transformation positionHash = Result positionHash -> Result positionHash -- | Mutator. negateFitnessOfResult :: Transformation positionHash negateFitnessOfResult result@MkResult { getQuantifiedGame = quantifiedGame } = result { getQuantifiedGame = Evaluation.QuantifiedGame.negateFitness quantifiedGame } -- | Mutator. addNPositionsToResult :: Type.Count.NPositions -> Transformation positionHash addNPositionsToResult nPositions result@MkResult { getNPositionsEvaluated = nPositionsEvaluated } = Control.Exception.assert (nPositions > 0) result { getNPositionsEvaluated = nPositions + nPositionsEvaluated }