author | Markus Bröker <mbroeker@largo.homelinux.org> |
Sat, 13 Dec 2008 13:41:38 +0100 | |
changeset 3 | 673c7ef3411e |
parent 0 | e0dbaef72362 |
child 4 | 429128ca9812 |
permissions | -rw-r--r-- |
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/** |
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* $Id: KIBoard.java 144 2008-04-25 13:09:35Z mbroeker $ |
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* $URL: http://localhost/svn/eclipse/Schachspiel/trunk/org/homelinux/largo/checkers/KIBoard.java $ |
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*/ |
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package org.homelinux.largo.checkers; |
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import org.homelinux.largo.games.board.Move; |
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import org.homelinux.largo.games.board.checkersboard.CheckersBoard; |
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public class KIBoard extends CheckersBoard { |
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static final long serialVersionUID = 250408; |
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static final int game_const = 500; |
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protected boolean SIMU_DEBUG = false; |
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private boolean negate_estimation = false; |
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private Move bestMove; |
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private int desired_depth; |
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public KIBoard(int w, int h) { |
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super(w, h); |
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desired_depth = -1; |
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} |
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/** |
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* Set the current DEBUG-Level: |
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* simu: print all valid, simulated moves |
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* undo: print all undos |
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*/ |
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public void setDebug(boolean simu, boolean undo) { |
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SIMU_DEBUG = simu; |
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UNDO_DEBUG = undo; |
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} |
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public boolean simu_debug() { |
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return SIMU_DEBUG; |
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} |
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public boolean undo_debug() { |
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return UNDO_DEBUG; |
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} |
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* This function flips the sides: Player A maximizes and Player B minimizes |
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*/ |
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public void negateEstimation(boolean b) { |
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negate_estimation = b; |
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} |
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/** |
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* The Minimax-Algorithm works for TWO-PLAYER Games |
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* Player A minimizes, Player B maximizes |
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*/ |
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public int estimateFunction() { |
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int i; |
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int white = 0; |
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int black = 0; |
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for(i=0;i<64;i++) { |
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if (isWhite(i)) |
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white+=getValue(i); |
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if (isBlack(i)) |
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black+=getValue(i); |
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} |
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/** |
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* solves ticket #3 |
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*/ |
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if ( negate_estimation ) |
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return white-black; |
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return black-white; |
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} |
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/** |
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* simulates and returns the next possible move for a Player or null, when no more moves are possible. |
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* The Turn will flip automatically if "simulate(...)" founds a valid move. |
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*/ |
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Move simulate(int t, int o) { |
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Move move = null; |
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int value; |
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if ( validTurn(o) ) { |
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while ( t < 64 ) { |
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if (!simulateMove(t, o) ) { |
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t++; |
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continue; |
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} |
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value = estimateFunction(); |
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move = new Move(value, t, o); |
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/* Flip Sides */ |
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setBlacksTurn(!isBlacksTurn()); |
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return move; |
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} |
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} |
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return null; |
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} |
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/** |
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* AlphaBeta-Algorithm: the Maximizer |
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*/ |
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int max_alpha_beta (int depth, int alpha, int beta) { |
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int moveValue; |
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int o, t; |
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Move move = null; |
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if ( desired_depth == -1 ) |
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desired_depth = depth; |
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for (o = 0; o < 64; o++) { |
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t=0; |
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while ( (move=simulate(t, o)) != null ) { |
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/* particular move from black */ |
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t = move.target; |
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if ( depth == 0 || Math.abs(move.value) > game_const ) |
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moveValue = move.value; |
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else /* best next move */ |
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moveValue = min_alpha_beta(depth-1, alpha, beta); |
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123 |
|
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undo(); |
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t++; |
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126 |
|
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if ( moveValue >= beta ) |
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return beta; |
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129 |
|
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if ( moveValue > alpha ) { |
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alpha = moveValue; |
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if ( depth == desired_depth ) |
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bestMove = move; |
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} |
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135 |
} |
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136 |
} |
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137 |
|
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return alpha; |
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139 |
} |
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140 |
|
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/** |
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* AlphaBeta-Algorithm: the Minimizer |
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*/ |
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int min_alpha_beta(int depth, int alpha, int beta) { |
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int moveValue; |
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int o, t; |
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Move move = null; |
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148 |
|
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for (o = 0; o < 64; o++) { |
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t=0; |
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while ( (move=simulate(t, o)) != null ) { |
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/* particular move from white */ |
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t = move.target; |
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154 |
|
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if ( depth == 0 || Math.abs(move.value) > game_const ) |
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moveValue = move.value; |
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else /* best next move */ |
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moveValue = max_alpha_beta(depth-1, alpha, beta); |
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159 |
|
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undo(); |
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t++; |
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162 |
|
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if ( moveValue <= alpha ) |
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return alpha; |
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165 |
|
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if ( moveValue < beta ) |
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beta = moveValue; |
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} |
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169 |
} |
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170 |
|
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return beta; |
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172 |
} |
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173 |
|
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174 |
/** |
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* Evaluates the next, best Move after search_depth half-moves. |
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* When the Machine has Black, set negateEstimation(false); |
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* When the Machine has White, set negateEstimation(true); |
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*/ |
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public boolean doBestMove(int search_depth) { |
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int value; |
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181 |
|
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182 |
desired_depth = -1; |
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183 |
bestMove = null; |
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value = max_alpha_beta(search_depth, Integer.MIN_VALUE, Integer.MAX_VALUE); |
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185 |
|
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186 |
if ( bestMove == null ) { |
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187 |
System.err.println("Computing once more..."); |
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188 |
value = max_alpha_beta(1, Integer.MIN_VALUE, Integer.MAX_VALUE); |
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189 |
if (bestMove == null) { |
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190 |
System.out.println("Finito"); |
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191 |
return false; |
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192 |
} |
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193 |
} |
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194 |
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195 |
if (doMove(bestMove.target, bestMove.origin)) { |
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196 |
System.out.println("Next Move"); |
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197 |
return true; |
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198 |
} |
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199 |
|
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200 |
return false; |
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201 |
} |
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202 |
} |