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Chain⼊⾨
goodbaton
Chain
Twitterで#chain_easy, #chain_hard で⾒つかります
普通は、追加されるブロックはランダムだが、

今回は、追加されるブロックが与えられます。
Chainとは
同じ⾊が2つ以上繋がっている場
合消すことが出来る
消すと上のブロックは下に移動
列にブロックが無くなると右から
左へと詰める
消す操作は50回まで
Chainの得点計算
1度に消した数をNとする
基本スコア … (N-1)*10
追加スコア … 押したブロックと同
時に消えたブロックとのマンハッ
タン距離の総和*10
列ボーナス … ブロックが無くなっ
た列数の2乗*100
Chainの得点計算
基本スコア …10
追加スコア … (0+1)*10
列ボーナス … 1*1*100
Chain
実演
Chain AIについて
goodbaton
アルゴリズム
局所探索法 / 焼きなまし法
禁断探索法 / 誘導局所探索法
部分最適化法 / 多ラベル法
貪欲ランダム適応型探索法
蟻群⽣法 / 遺伝的アルゴリズム
アルゴリズム
局所探索法 / 焼きなまし法
禁断探索法 / 誘導局所探索法
部分最適化法 / 多ラベル法
貪欲ランダム適応型探索法
蟻群⽣法 / 遺伝的アルゴリズム
使いづらい
アルゴリズム①
ビームサーチもどきを書く
幅のある貪欲法
乱数を使⽤ -> スコア上昇

→ 貪欲ランダム適応型探索法
貪欲ランダム適応型探索法
別名 GRASP法
貪欲法にランダム性を加えた⽅法
評価値の良い物複数からひとつをランダムで選ぶ
アルゴリズム②
chokudaiサーチ(?)
時間無制限だとメモリの⼤量使⽤がかなり⾟い
10秒ぐらいだとちょうど良い
chokudaiサーチ(?)
DATA(turn1)
…
Heap1 Heap2 Heap3 Heap 51
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-1)
DATA(turn2-2)
DATA(turn2-3)
DATA(turn2-4)
DATA(turn1)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-1)
DATA(turn2-2)
DATA(turn2-3)
DATA(turn2-4)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-1)
DATA(turn2-2)
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-1)
DATA(turn3-2)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-2)
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-1)
DATA(turn3-2)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-2)
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-1)
DATA(turn3-5)
DATA(turn3-7)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-1)
DATA(turn3-5)
DATA(turn3-7)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-1)
DATA(turn3-5)
DATA(turn3-7)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-7)
DATA(turn3-3)
1周⽬
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-7)
DATA(turn3-3)
1周⽬
DATA(end)
DATA(end)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-7)
DATA(turn3-3)
2周⽬
DATA(end)
DATA(end)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-3)
DATA(turn2-4)
DATA(turn3-9)
DATA(turn3-3)
2周⽬
DATA(end)
DATA(end)
DATA(turn3-7)
DATA(turn3-8)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-4)
DATA(turn3-9)
DATA(turn3-3)
2周⽬
DATA(end)
DATA(end)
DATA(turn3-7)
DATA(turn3-8)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-4) DATA(turn3-3)
2周⽬
DATA(end)
DATA(end)
DATA(turn3-7)
DATA(turn3-8)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-4) DATA(turn3-3)
2周⽬
DATA(end)
DATA(end)
DATA(turn3-7)
DATA(turn3-8)
DATA(end)
DATA(end)
chokudaiサーチ(?)
…
Heap1 Heap2 Heap3 Heap 51
DATA(turn2-4) DATA(turn3-3)
n周⽬
DATA(end)
DATA(end)
DATA(turn3-7)
DATA(turn3-8)
DATA(end)
DATA(end)
アルゴリズム③
ビームサーチを2つ使⽤
消費メモリ少なくて幸せ
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn2-1)
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn2-1)
DATA(turn16)
DATA(turn3)
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn2-1)
DATA(turn16)
DATA(turn3)
Score
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn16)
DATA(turn3)
DATA(turn2-1)
Score
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn2-1)
Score
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn1)
DATA(turn2-1)
Score
DATA(turn2-2)
DATA(turn16)
DATA(turn3)
アルゴリズム③ 詳細
Beam Search 1 Beam Search 2
DATA(turn28-1)
Score
DATA(turn43)
DATA(turn29)
DATA(turn28-9)
Score
DATA(turn28-6)
Score
DATA(turn28-3)
評価関数
⼀番多い⾊が、2,3番⽬の⾊の数とどれだけ差があるか
⼀⾊のみの列がいくつあるか
乱数により加点
評価関数
⼀番多い⾊が、2,3番⽬の⾊の数とどれだけ差があるか
⼀⾊のみの列がいくつあるか
乱数により加点
重み
結果
easy_1|44680
easy_2|41120
easy_3|41510
easy_4|50580
easy_5|39510
hard_1|14030
hard_2|13520
hard_3|13150
hard_4|14050
hard_5|13030
まとめ
学んだことを使いたかった
もう少し、評価関数を考えれば良くなりそう
tozanさん強い

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