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Algorithm Development Kit 1.0 |
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java.lang.Objectalgs.model.gametree.debug.NegMaxEvaluation
public class NegMaxEvaluation
Represents an Intelligent Tic Tac Toe playing agent that uses the NegMax algorithm to select a move. This implementation is quite different from the non-debug version; this was done because of the convoluted nature of the debugging code to generate the game trees. After execution, the debug information is properly invoked on the provided IDebugSearch interface.
Constructor Summary | |
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NegMaxEvaluation(int ply)
Create an evaluator with the given state. |
Method Summary | |
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IGameMove |
bestMove(IGameState state,
IPlayer player,
IPlayer opponent)
Initiates the MiniMax computations by determining the maximum number of moves in advance to look. |
void |
debug(IDebugSearch debug)
Install debugger to use. |
java.lang.String |
toString()
Expose board state as string (useful for debugging purposes). |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public NegMaxEvaluation(int ply)
bestMove
is invoked.
ply
- Depth to search.Method Detail |
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public IGameMove bestMove(IGameState state, IPlayer player, IPlayer opponent)
bestMove
in interface IEvaluation
state
- Game state being evaluated.player
- The player making the next move.opponent
- Opponent of player who will make counter movespublic java.lang.String toString()
toString
in class java.lang.Object
public void debug(IDebugSearch debug)
debug
- debugger to use.
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