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コンピュータとオセロ対戦49 ~AI実装と性能評価~

前回

今回の目標

前回作成したネットワークを使用して対戦AIを作る。
また、34 ~性能評価~のように、その強さを客観的に評価する。

使用バージョン

  • Java 17.0.1
  • MyNet 1.2.4

ここから本編

対戦AIを作る

まずは前回作成したネットワークを使えるようにしていきます。
なお、ここではそのネットワークを「oseroAI.net」という名前に変更しています。

クラス構成

四つの引数を受け取り、倍精度実数を返す関数を格納するFourFunctionクラスも使用しています。
OseroBaseとOseroクラスについては、前回から変更していません。

OseroBase  // オセロの基本機能を実装
↓ 継承
Osero      // オセロの思考方法を実装
↓ 継承
OseroAI    // オセロAIを実装

OseroAI.java

オセロAIを実装する。基本的には33 ~勝敗予測AIと対戦~(Pythonでやった時)と大差ないが、探索をOseroクラスのexploreAssistに任せ、スコアを返すアルゴリズムをそのメソッドに渡しています。
また、対戦結果を返すplayAndGetResultメソッドを作成しました。
なお、コンストラクタで必ずネットワークの名前を指定する必要があります。
他に特筆すべきことはないので、全文載せます。

OseroAI.java
OseroAI.java
import java.util.function.BiConsumer;
import java.util.ArrayList;

import org.MyNet.network.*;
import org.MyNet.nodes.activationFunction.*;
import org.MyNet.layer.*;
import org.MyNet.matrix.*;

public class OseroAI extends Osero {
    protected static Network net = null;

    public OseroAI(ArrayList<BiConsumer<long[], Boolean>> playMethod, String netName){
        this.setup();
        this.playMethod = playMethod;
        this.loadNet(netName);
    }

    public OseroAI(BiConsumer<long[], Boolean> black, BiConsumer<long[], Boolean> white, String netName){
        this.setup();
        this.playMethod.add(black);
        this.playMethod.add(white);
        this.loadNet(netName);
    }

    public int[] playAndGetResult(){
        boolean can = true, oldCan = true;

        while ((can = this.checkAll()) || oldCan){
            if (can){
                this.playMethod.get(this.turn ? 1:0).accept(this.bw, this.turn);
            }

            this.turn = !this.turn;
            oldCan = can;
        }

        int[] rtn = {this.popCount(this.bw[0]), this.popCount(this.bw[1])};
        return rtn;
    }

    protected void loadNet(String netName){
        net = new Network(
            192,
            new Input(100, AF.RELU),
            new Dense(50, AF.SIGMOID),
            new Output(1, AF.RELU)
        );
        net.load(netName);
    }

    public static void oseroAI(long board[], boolean turn){
        Osero.exploreAssist(board, turn, OseroAI::exploreAI);
    }

    protected static double exploreAI(long[] board, boolean nowTurn, boolean turn, int num){
        if (num >= Osero.readGoal[(nowTurn ? 1:0)]) return OseroAI.predict(board, nowTurn);

        double score = 0, placeNum = 0;
        int row = -1, col = 0;
        long[] boardLeaf = new long[2];
        for (int place = 0; place < OseroBase.SIZE << OseroBase.SHIFTNUM; place++){
            row++;
            if (row >= OseroBase.SIZE){
                row = 0;
                col++;
            }
            if (!OseroBase.check(row, col, board, turn)) continue;
            placeNum += 1;
            boardLeaf[0] = board[0]; boardLeaf[1] = board[1];
            OseroBase.put(row, col, boardLeaf, turn);
            score += OseroAI.exploreAI(
                boardLeaf,
                nowTurn,
                !turn,
                num + 1    
            );
        }
        
        if (placeNum > 0) return score / placeNum;
        else              return OseroAI.predict(board, nowTurn);
    }

    protected static double predict(long board[], boolean turn){
        Matrix x;
        ArrayList<ArrayList<Double>> x_list = new ArrayList<ArrayList<Double>>();
        x_list.add(new ArrayList<Double>());

        long place = 1;
        int my, opp;
        boolean myStone, oppStone;

        if (turn){
            my = 1; opp = 0;
        }else{
            my = 0; opp = 1;
        }

        while (place != 0){
            x_list.get(0).add((myStone = ((board[my] & place) != 0)) ? 1.0 : 0.0);
            x_list.get(0).add((oppStone = ((board[opp] & place) != 0)) ? 1.0 : 0.0);
            x_list.get(0).add(myStone || oppStone ? 0.0 : 1.0);
            place = place << 1;
        }

        x = new Matrix(x_list);

        return OseroAI.net.forward(x).matrix[0][0];
    }
}

Run.java

OseroAIクラスをインスタンス化し、一度試合を行います。

Run.java
public class Run {
    public static void main(String[] str){
        Osero run = new OseroAI(OseroAI::oseroAI, OseroAI::oseroAI, "oseroAI.net");
        run.play(Osero.PRINT);
    }
}

実行結果

対戦結果を載せますが、長いので気になる人だけ見てください。
人力でチェックしたところ、一応おかしな点はありませんでした。

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7|  |  |@ |@ |@ |  |  |  |
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8|  |  |@ |  |  |  |  |  |
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4|  |@ |@ |O |@ |O |  |  |
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3|  |O |@ |O |O |@ |O |  |
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4|  |@ |@ |O |@ |O |  |O |
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5|@ |O |O |O |O |O |O |  |
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6|  |@ |@ |@ |@ |  |  |  |
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3|  |O |@ |O |O |@ |O |  |
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4|  |@ |@ |O |@ |O |  |O |
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6|  |@ |@ |O |@ |  |  |  |
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6|  |@ |@ |O |@ |@ |  |O |
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4|  |@ |@ |@ |@ |O |  |@ |
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6|  |@ |@ |O |@ |@ |  |O |
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6|  |@ |@ |O |@ |@ |  |O |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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4|  |@ |@ |@ |O |@ |  |@ |
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5|@ |@ |@ |@ |O |@ |@ |@ |
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6|  |@ |@ |O |O |@ |  |O |
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7|  |  |O |O |O |  |  |  |
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8|  |O |O |O |O |  |  |  |
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1|@ |@ |@ |O |  |O |  |  |
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2|@ |@ |@ |@ |O |O |  |  |
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3|  |@ |@ |O |O |@ |@ |@ |
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4|  |@ |@ |@ |O |@ |  |@ |
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5|@ |@ |@ |@ |O |@ |@ |@ |
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6|  |@ |@ |O |O |@ |  |O |
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1|@ |@ |@ |O |  |O |  |  |
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6|  |@ |O |O |O |@ |  |O |
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8|  |O |O |O |O |  |  |  |
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1|@ |@ |@ |O |  |O |  |  |
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3|  |O |@ |O |O |@ |@ |@ |
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4|O |O |O |O |O |@ |  |@ |
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5|@ |O |@ |@ |O |@ |@ |@ |
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6|  |@ |O |O |@ |@ |  |O |
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7|  |  |O |O |O |@ |  |  |
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8|  |O |O |O |O |  |  |  |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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4|O |O |O |O |O |@ |  |@ |
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6|  |O |O |O |@ |@ |  |O |
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4|@ |O |O |O |O |@ |  |@ |
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5|@ |O |O |@ |O |@ |@ |@ |
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6|  |O |O |O |@ |@ |  |O |
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7|O |  |O |O |O |@ |  |  |
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8|  |O |O |O |O |  |  |  |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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3|@ |@ |@ |O |O |@ |@ |@ |
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4|@ |O |O |O |O |@ |  |@ |
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5|@ |O |O |@ |O |@ |@ |@ |
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6|  |O |O |O |@ |O |  |O |
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7|O |  |O |O |O |O |O |  |
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8|  |O |O |O |O |  |  |  |
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1|@ |@ |@ |O |  |O |  |  |
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3|@ |@ |@ |O |O |@ |@ |@ |
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4|@ |O |O |@ |O |@ |  |@ |
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5|@ |O |O |@ |@ |@ |@ |@ |
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6|  |O |O |O |@ |@ |  |O |
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7|O |  |O |O |O |O |@ |  |
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8|  |O |O |O |O |  |  |@ |
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1|@ |@ |@ |O |  |O |  |  |
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4|@ |O |O |@ |O |O |O |@ |
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5|@ |O |O |@ |@ |O |@ |@ |
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6|  |O |O |O |O |@ |  |O |
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7|O |  |O |O |O |O |@ |  |
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8|  |O |O |O |O |  |  |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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2|@ |@ |O |@ |O |O |  |  |
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3|@ |@ |@ |O |O |O |@ |@ |
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4|@ |O |O |@ |O |O |O |@ |
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5|@ |O |O |@ |@ |O |@ |@ |
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6|  |O |O |O |@ |@ |  |O |
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1|@ |@ |@ |O |  |O |  |  |
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6|  |O |O |O |@ |@ |  |O |
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8|  |O |O |O |O |  |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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2|@ |@ |@ |@ |O |O |  |  |
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3|@ |@ |@ |@ |O |O |@ |@ |
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4|@ |O |O |@ |@ |O |O |@ |
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5|@ |O |O |@ |@ |@ |@ |@ |
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6|  |O |O |O |@ |@ |@ |O |
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7|O |  |O |O |O |O |@ |O |
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8|  |O |O |O |O |  |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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2|@ |@ |@ |@ |O |O |  |  |
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3|@ |@ |@ |@ |O |O |@ |@ |
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4|@ |O |O |@ |@ |O |O |@ |
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5|@ |O |O |@ |@ |@ |@ |@ |
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6|  |O |O |O |@ |@ |@ |O |
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7|O |  |O |O |O |O |O |O |
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8|  |O |O |O |O |O |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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6|  |O |O |O |@ |@ |@ |O |
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7|O |  |O |O |O |O |O |O |
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8|@ |@ |@ |@ |@ |@ |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |O |  |O |  |  |
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2|@ |@ |@ |@ |O |O |  |O |
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3|@ |@ |@ |@ |O |O |O |O |
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4|@ |O |O |@ |@ |O |O |O |
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5|@ |O |O |@ |@ |@ |@ |O |
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6|  |O |O |O |@ |@ |@ |O |
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7|O |  |O |O |O |O |O |O |
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8|@ |@ |@ |@ |@ |@ |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |@ |@ |O |  |  |
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2|@ |@ |@ |@ |@ |O |  |O |
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3|@ |@ |@ |@ |@ |O |O |O |
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4|@ |O |O |@ |@ |O |O |O |
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5|@ |O |O |@ |@ |@ |@ |O |
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6|  |O |O |O |@ |@ |@ |O |
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7|O |  |O |O |O |O |O |O |
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8|@ |@ |@ |@ |@ |@ |@ |@ |
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   1  2  3  4  5  6  7  8
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1|@ |@ |@ |@ |@ |O |  |  |
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2|@ |@ |@ |@ |@ |O |  |O |
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3|@ |@ |@ |@ |@ |O |O |O |
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4|@ |O |@ |@ |@ |O |O |O |
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5|@ |@ |O |@ |@ |@ |@ |O |
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6|@ |@ |@ |@ |@ |@ |@ |O |
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7|@ |  |O |O |O |O |O |O |
 -------------------------
8|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------

   1  2  3  4  5  6  7  8
 -------------------------
1|@ |@ |@ |@ |@ |O |  |  |
 -------------------------
2|@ |@ |@ |@ |@ |O |  |O |
 -------------------------
3|@ |@ |@ |@ |@ |O |O |O |
 -------------------------
4|@ |O |@ |@ |O |O |O |O |
 -------------------------
5|@ |O |O |O |@ |@ |@ |O |
 -------------------------
6|@ |O |O |@ |@ |@ |@ |O |
 -------------------------
7|@ |O |O |O |O |O |O |O |
 -------------------------
8|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------

   1  2  3  4  5  6  7  8
 -------------------------
1|@ |@ |@ |@ |@ |O |  |  |
 -------------------------
2|@ |@ |@ |@ |@ |@ |@ |O |
 -------------------------
3|@ |@ |@ |@ |@ |@ |@ |O |
 -------------------------
4|@ |O |@ |@ |@ |O |@ |O |
 -------------------------
5|@ |O |O |@ |@ |@ |@ |O |
 -------------------------
6|@ |O |@ |@ |@ |@ |@ |O |
 -------------------------
7|@ |@ |O |O |O |O |O |O |
 -------------------------
8|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------

   1  2  3  4  5  6  7  8
 -------------------------
1|@ |@ |@ |@ |@ |O |O |  |
 -------------------------
2|@ |@ |@ |@ |@ |O |O |O |
 -------------------------
3|@ |@ |@ |@ |O |@ |O |O |
 -------------------------
4|@ |O |@ |O |@ |O |O |O |
 -------------------------
5|@ |O |O |@ |@ |@ |O |O |
 -------------------------
6|@ |O |@ |@ |@ |@ |O |O |
 -------------------------
7|@ |@ |O |O |O |O |O |O |
 -------------------------
8|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------

   1  2  3  4  5  6  7  8
 -------------------------
1|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------
2|@ |@ |@ |@ |@ |O |@ |@ |
 -------------------------
3|@ |@ |@ |@ |O |@ |O |@ |
 -------------------------
4|@ |O |@ |O |@ |O |O |@ |
 -------------------------
5|@ |O |O |@ |@ |@ |O |@ |
 -------------------------
6|@ |O |@ |@ |@ |@ |O |@ |
 -------------------------
7|@ |@ |O |O |O |O |O |@ |
 -------------------------
8|@ |@ |@ |@ |@ |@ |@ |@ |
 -------------------------
black: 47, white: 17
black win!

対戦を行う

これまでに登場した思考方法を総当たりで戦わせます。

Run.java

random、nHand、nHandCustom、nLeast、nMost、oseroAIを、それぞれ1手先、2手先までの計12種類の思考方法を総当たりで戦わせます。
さらに、Pythonよりも実行速度が速いので、それぞれの条件で乱数のシード値を変更し100通りの試合を行います。
よって、12x12x100の14400試合行います。
34 ~性能評価~では一回ずつしか戦わせられなかったので、この時より正確なデータが得られると思います。
プログラムは、これらを戦わせて結果をcsv出力させているだけなので興味ある方だけ見てみてください。

プログラム
Run.java
import java.util.function.BiConsumer;
import java.util.ArrayList;
import java.io.IOException;
import java.io.PrintWriter;

public class Run {
    public static void main(String[] str){
        ArrayList<BiConsumer<long[], Boolean>> playMethod;
        playMethod = new ArrayList<BiConsumer<long[], Boolean>>();
        ArrayList<String> playMethodName;
        playMethodName = new ArrayList<String>();
        ArrayList<Integer> readGoals;
        readGoals = new ArrayList<Integer>();

        playMethod.add(Osero::random);	playMethodName.add("random");	readGoals.add(1);
        playMethod.add(Osero::random);	playMethodName.add("random");	readGoals.add(2);
        playMethod.add(Osero::nHand);	playMethodName.add("nHand");	readGoals.add(1);
        playMethod.add(Osero::nHand);	playMethodName.add("nHand");	readGoals.add(2);
        playMethod.add(Osero::nHandCustom);	playMethodName.add("nHandCustom");	readGoals.add(1);
        playMethod.add(Osero::nHandCustom);	playMethodName.add("nHandCustom");	readGoals.add(2);
        playMethod.add(Osero::nLeast);	playMethodName.add("nLeast");	readGoals.add(1);
        playMethod.add(Osero::nLeast);	playMethodName.add("nLeast");	readGoals.add(2);
        playMethod.add(Osero::nMost);	playMethodName.add("nMost");	readGoals.add(1);
        playMethod.add(Osero::nMost);	playMethodName.add("nMost");	readGoals.add(2);
        playMethod.add(OseroAI::oseroAI);	playMethodName.add("oseroAI");	readGoals.add(1);
        playMethod.add(OseroAI::oseroAI);	playMethodName.add("oseroAI");	readGoals.add(2);
        
        OseroAI run = new OseroAI(OseroAI::oseroAI, OseroAI::oseroAI, "oseroAI.net");

        try(
            PrintWriter fp = new PrintWriter("data.csv");
        ){
            int[] result;
            fp.write("black_method,white_method,black_score,white_score,black_read_goal,white_read_goal,seed\n");

            for (int i = 0; i < playMethod.size(); i++){
                System.out.printf("\r%d/%d", i+1, playMethod.size());
                for (int j = 0; j < playMethod.size(); j++){
                    run.setPlayMethod(playMethod.get(i), playMethod.get(j));
                    run.setReadGoal(readGoals.get(i), readGoals.get(j));
                    for (int k = 0; k < 100; k++){
                        run.setRandom(k);
                        run.setup();
                        result = run.playAndGetResult();

                        fp.printf(
                            "%s,%s,%d,%d,%d,%d,%d\n",
                            playMethodName.get(i),
                            playMethodName.get(j),
                            result[0],
                            result[1],
                            readGoals.get(i),
                            readGoals.get(j),
                            k
                        );
                    }
                }
            }

            System.out.println();
        }catch (IOException e){
            System.out.println("IO Exception");
            System.exit(-1);
        }
    }
}

対戦結果

対戦結果を見てみます。
グラフ作成プログラムは以下の通り。

グラフ作成プログラム
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

sns.set()

################################################

def bar(x, y, xlabel, ylabel, fig_name, dir_name):
    fig, ax = plt.subplots(figsize=(8, 8))
    rect = plt.bar(x, y, color="g")
    rect[[num for num, y_ele in enumerate(y) if max(y) == y_ele][0]].set_color("r")
    rect[[num for num, y_ele in enumerate(y) if min(y) == y_ele][0]].set_color("b")
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.title(fig_name)
    plt.savefig(dir_name + "/" + fig_name + ".png")
    plt.clf()
    plt.close()

################################################

df = pd.read_csv("data.csv")
methods_name = df["black_method"].unique()

################################################

# 勝ち星の数

y = []

for method in methods_name:
    num = 0
    num += len(df.query("black_method=='%s'" % method).query("black_score>white_score"))
    num += len(df.query("white_method=='%s'" % method).query("white_score>black_score"))
    y.append(num)

bar(methods_name, y, "method name", "win num", "win num each method name", "fig")

他のグラフもほぼ同じプログラムで作っているのでプログラムは省略します。
なお、トップを赤、ワーストを青、その他を緑色で着色しています。

勝ち星の数

win num each method name.png

参考までに、34 ~性能評価~の結果はこちら。

image.png

34ではnleastが猛威を振るいましたが、今回のトップはnHandCustomとなりました。nLeastは二番手につけています。
また、せっかく作成したAIは今回最下位に。
34の結果は総当たりで1回ずつ戦ったものですので、データ量100倍の今回の結果の方が信用できると思います。

負け星の数

lose num each method name.png

image.png

勝ち星グラフを裏返したような形。
引き分けはほぼなかったようです。

獲得石数

score num each method name.png

image.png

勝ち星ほど大差にはならなかったというのは34と同じ結果。
ただ34と違い、順位は逆転していません。

1手先と2手先

win num each read goal.png

僅差で2が勝利。
あまり変わらないようです。

各手法とreadGoal

win num each method name and read goal.png

randomは1も2も同じ思考方法なので気にしないでください。むしろほぼ同じ結果で安心しました。
トップは1handCustom、ワーストは1oseroAIでした。
以外にも1handCustomの方が2handCustomより多く勝ち星を得る結果に。
他の手法を見ると、

  • nHand 1 < 2
  • nHandCustom 1 > 2
  • nLeast 1 > 2
  • nMost 1 ≒ 2
  • oseroAI 1 < 2

でした。
さらに言えば、トップ層の思考方法は1手先まで読む方が強く、ワースト層は2手先まで読む方が強かったです。偶然でしょうか。

シード値の公平性

各シード値で、黒が勝った数-白が勝った数を計算しグラフ化しました。

seed fairness.png

各シードで12*12の144試合行っていますから、もっとも差の大きいところでは、黒が約90試合勝利したのに対し、白はわずか約50試合しか勝利していません。およそ2倍の差。

いろいろなデータを見てみたところ、以下のようになりました。

import numpy as np

np_y = np.array(y)

print("最小値\t%d" % np_y.min())
print("中央値\t%d" % np.median(np_y))
print("最大値\t%d" % np_y.max())
print("平均\t%f" % np_y.mean())
print("分散\t%f" % np_y.var())
print("標準偏差\t%f" % np_y.std())
最小値	-32
中央値	3
最大値	42
平均	4.090000
分散	227.161900
標準偏差	15.071891

平均と中央値が0に近いので、一応全体としてはまあまあ公平といえるのではないでしょうか。
標準偏差15という数字ですが、グラフを見る限りではバラツキとして大きいように思います。

まとめ

現行の方法で強いAIを作りたいなら、何か工夫が必要そう。
nLeastと組み合わせてもあまり強くはならないだろう。

フルバージョン

次回は

次回やることはまだ決まっていません。
理由は、MyNetの高速化をしたいと考えているため、また、次の方針がまだ決まっていないためです。

次回

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