December 2016
Intermediate to advanced
440 pages
9h 44m
Japanese
Content preview from アルゴリズムクイックリファレンス 第2版
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206
■
7
章
AI
における経路探索
ぜなら、まったく同じ手を見つけるからだ。唯一の違いは、
MIN
とラベル付けされ
ていた層における値が、
ネグマックス
では、負になっていることである。図7-6と図
7-3の木を比較すれば、この振る舞いがわかるだろう。
図7-6 ネグマックスのゲーム木の例
7.4.1
解
例7-3では、
MoveEvaluation
の点数が、一貫してその手を打つプレイヤーの観点
からのゲーム状態の評価になっていることに注意。手番のプレイヤーに対する評価
を改めることで、アルゴリズムの実装が単純になっている。
例
7-3
ネグマックスの実装
public class NegMaxEvaluation implements IEvaluation {
IGameState state; /*
探索の途中で変更される状態
*/
int ply; /*
読みの深さ。どれだけ探索を続けるか。
*/
public NegMaxEvaluation (int ply) {
this.ply = ply;
}
public IGameMove bestMove (IGameState s, IPlayer player
, IPlayer opponent)
{
state = s.copy();
MoveEvaluation me = negmax(ply, player, opponent);
return me.move;
}
public MoveEvaluation negmax (int ...
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