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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198
■
7
章
AI
における経路探索
場合には、拡張深さの限度を設定すると、地平線のすぐ向こうの解が見つからない。
7.3
ミニマックス
先手の観点でゲーム木のある特定の位置が与えられたとき、探索プログラムは、
勝利の可能性が最大になる（少なくとも引き分けになる）ような手を見つけなければ
ならない。現在のゲーム状態と、この状態での可能な手だけを考慮するのではなく、
プログラムは、打った手に対して相手がどのような手を打ち返すかをも考慮しなけ
ればならない。プログラムは、プレイヤーの観点からゲーム状態の評価を整数で返
す、評価関数
score(state, player)
が既にあるものと仮定する。低い点数（負のこ
ともある）は、弱いゲーム状態を反映する。
ゲーム木は、
n
手先の将来のゲーム状態を考慮して展開される。木の各層におい
て、
MAX
層（ここでは、ゲーム状態の評価点数を最大化することでプレイヤーを
有利にすることが目標となる）と
MIN
層（ここでは、ゲーム状態の評価点数を最小
化することで相手側を有利にすることが目標）とが交互に出現する。これは、プロ
グラムが、プレイヤーの手番で
score(state, initial)
を最大化する手を選び、相
手側の手番では、相手が賢くて
score(state, initial)
を最小化する手を選ぶもの
と想定するからだ。
もちろん、プログラムは、有限個数の手までしか先読みできず、先読みをした余
分な手は、莫大なメモリと時間を使用する。先読みで選ばれた手の個数は、読みの ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.