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package ai.libs.jaicore.search.algorithms.mdp.mcts.thompson;
import java.util.Random;
import ai.libs.jaicore.search.algorithms.mdp.mcts.IPolicy;
import ai.libs.jaicore.search.algorithms.mdp.mcts.MCTS;
import ai.libs.jaicore.search.algorithms.mdp.mcts.UniformRandomPolicy;
import ai.libs.jaicore.search.probleminputs.IMDP;
public class DNGMCTS extends MCTS {
public DNGMCTS(final IMDP input, final double varianceFactor, final double initLambda, final int maxIterations, final double gamma, final double epsilon, final Random random, final boolean tabooExhaustedNodes, final boolean maximize) {
this(input, new UniformRandomPolicy<>(random), varianceFactor, initLambda, maxIterations, gamma, epsilon, tabooExhaustedNodes, maximize);
}
public DNGMCTS(final IMDP input, final IPolicy defaultPolicy, final double varianceFactor, final double initLambda, final int maxIterations, final double gamma, final double epsilon, final boolean tabooExhaustedNodes, final boolean maximize) {
super(input, new DNGPolicy<>(gamma, t -> {
try {
return input.isTerminalState(t);
} catch (InterruptedException e) {
Thread.currentThread().interrupt(); // re-interrupt!
return false;
}
}, varianceFactor, initLambda, maximize), defaultPolicy, maxIterations, gamma, epsilon, tabooExhaustedNodes);
}
}
