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Small improvements.
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@peng225
peng225 committed Dec 10, 2014
1 parent 0ad0938 commit e09c68d
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Showing 7 changed files with 72 additions and 389 deletions.
8 changes: 4 additions & 4 deletions Makefile
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Original file line number Diff line number Diff line change
@@ -1,11 +1,11 @@
#Makefile


# CFLAGS = -c -g -O3 -Wall -std=c++0x -flto -DNDEBUG -MMD -MP
# FINAL_CFLAGS = -g -O3 -Wall -std=c++0x -flto -DNDEBUG
CFLAGS = -c -g -O3 -Wall -std=c++0x -flto -DNDEBUG -MMD -MP
FINAL_CFLAGS = -g -O3 -Wall -std=c++0x -flto -DNDEBUG

CFLAGS := -c -g -O3 -Wall -std=c++0x -flto -MMD -MP
FINAL_CFLAGS := -g -O3 -Wall -std=c++0x -flto
# CFLAGS := -c -g -O3 -Wall -std=c++0x -flto -MMD -MP
# FINAL_CFLAGS := -g -O3 -Wall -std=c++0x -flto

# CFLAGS = -c -g -O0 -Wall -std=c++0x -MMD -MP
# FINAL_CFLAGS = -g -O0 -Wall -std=c++0x
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22 changes: 15 additions & 7 deletions include/learner.h
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Expand Up @@ -6,17 +6,28 @@
#include "pattern.h"
#include "ai.h"

const double LEARNING_RATE = 0.207;
const double GAMMA = 0.0717;
/* const double LEARNING_RATE = 0.207; */
/* const double GAMMA = 0.0717; */
/* const double ACCURACY = 0.327; */

const double LEARNING_RATE = 0.635;
const double GAMMA = 1.877;
const double ACCURACY = 1.999;

/* const int LOAD_KIFU_NUM = 260; */
const int LOAD_KIFU_NUM = 1;
/* const int LOAD_KIFU_NUM = 1; */
const int LOAD_KIFU_NUM = 50;

/* const int REPEAT_NUM = 10; */
/* const int REPEAT_NUM = 2; */
const int REPEAT_NUM = 2;
const double ACCURACY = 0.327;

const int THRESH_NUM_CUTOFF_MOVE = 4;
const int MAX_FILENAME = 32;

const int SHALLOW = 3;
const int DEEP = 5;

using std::vector;
using std::list;
using std::pair;
Expand All @@ -31,14 +42,11 @@ struct CorrectMove
this->board = board;
this->candList = candList;
correctPos = pos;
/* correctPos.first = x; */
/* correctPos.second = y; */
}

Board board;
list<BitBoard> candList;
BitBoard correctPos;
/* pair<int, int> correctPos; */
};

class Learner
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2 changes: 2 additions & 0 deletions include/menu.h
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Expand Up @@ -18,6 +18,8 @@ using std::string;
const int MAIN_AI = 0;
const int SUB_AI = 1;

const int LEARN_VERVOSE = 1;

extern void put(Board &board, list<History> &hist, const list<string> &args);
extern void search(Board &board, AI &ai, int depth, list<History> &hist);
extern void fight(Board &board, AI &ai, AI &subAI, const list<string> &args);
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3 changes: 2 additions & 1 deletion src/ai.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -337,7 +337,8 @@ MoveInfo AI::negascout(Board &board, double alpha, double beta, int depth,
}

// 学習時に使用
DetailedMoveInfo AI::detailedNegascout(Board &board, double alpha, double beta, int depth, const Pattern &lnPt)
DetailedMoveInfo AI::detailedNegascout(Board &board, double alpha, double beta,
int depth, const Pattern &lnPt)
{
DetailedMoveInfo info;

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63 changes: 38 additions & 25 deletions src/learner.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -59,6 +59,7 @@ void Learner::loadKifu()
tboard.display();
// 正解の指し手を保存していく
kyokumen.push_back(CorrectMove(tboard, tboard.getCl(), pos));
// kyokumen.push_back(CorrectMove(tboard, pos));
// boardを一手ずつ進めていく
// パスなら手順を入れ替えてやり直し
if(!board.putStone(pos, true)){
Expand All @@ -76,7 +77,7 @@ void Learner::loadKifu()
random_shuffle(kyokumen.begin(), kyokumen.end(), rnd);

std::cout << "Learning data randomized!" << std::endl;
std::cout << "Loaded kyokumen num:" << kyokumen.size() << std::endl;
std::cout << "Loaded kyokumen num: " << kyokumen.size() << std::endl;
}

// Bonanza method
Expand All @@ -96,50 +97,57 @@ void Learner::learn(std::string filename, bool verbose)
for(int h = 0; h < REPEAT_NUM; h++){
for(vector<CorrectMove>::iterator i = begin(kyokumen);
i != end(kyokumen); i++){
std::cout << "repeat:" << h << ", kyokumen:"
std::cout << "repeat: " << h << ", kyokumen: "
<< distance(begin(kyokumen), i) << std::endl;

if(verbose){
i->board.display();
}
int turn = i->board.getTurn();

// int turn = i->board.getTurn();
BitBoard cpos = i->correctPos;
std::string tlabel = (turn == BLACK ? "BLACK" : "WHITE");
std::string tlabel = (i->board.getTurn() == BLACK ? "BLACK" : "WHITE");
if(verbose){
std::cout << "turn:" << tlabel << std::endl;
std::cout << "turn: " << tlabel << std::endl;
pair<int, int> coord = Board::posToXY(cpos);
std::cout << "correct pos:" << coord.first << ", "
<< coord.second << std::endl;
std::cout << "correct pos: " << coord.first + 1 << ", "
<< coord.second + 1 << std::endl;
}

BitBoard revPattern;
revPattern = i->board.putStone(cpos);
//棋譜の手から深さ3or5の探索を行った局面の評価値を取得する
DetailedMoveInfo cv; //棋譜の手、評価値、末端局面を保持する
cv = ai.detailedNegascout(i->board, -INF, INF,
h < (REPEAT_NUM >> 1) ? 3 : 5, pt);
h < (REPEAT_NUM >> 1) ? SHALLOW : DEEP, pt);
cv.score *= -1;
cv.pos = cpos;
i->board.undo(cpos, revPattern);
// double cmbsValue = -sc.eval(cv.ban, -turn).value;
if(verbose){
// double cmbsValue = ai.detailedEval(cv.board, pt).score;
std::cout << "correct value:" << cv.score << std::endl;
std::cout << "correct value: " << cv.score << std::endl;
// std::cout << "must be same:" << cmbsValue << std::endl;
// assert(cv.score == cmbsValue || cv.score == -cmbsValue);

std::cout << "correct terminal situation:" << std::endl;
std::cout << "correct terminal situation: " << std::endl;
cv.board.display();
}

//棋譜の手から探索を行った末端局面の特徴ベクトルを抽出
cvalidIndices.clear();
// bkCvalidIndices.clear();
pt.extractFeatureIndices(cv.board, cvalidIndices);
// bkCvalidIndices.assign(cvalidIndices.begin(), cvalidIndices.end());

// for(list<BitBoard>::const_iterator j = begin(i->board.getCl());
// j != end(i->board.getCl()); j++){
/*
i->board.getCl()を直接呼ぶことはできない。
board内のcandListはputStoneやundoによって内部的に変化しており、
イテレータが不正な値を指すことになるから。
*/
for(list<BitBoard>::const_iterator j = begin(i->candList);
j != end(i->candList); j++){
j != end(i->candList); j++){
//棋譜の手なら飛ばす
// if(cv.x == j->first && cv.y == j->second){
if(cv.pos == *j){
continue;
}
Expand All @@ -148,19 +156,19 @@ void Learner::learn(std::string filename, bool verbose)
revPattern = i->board.putStone(*j);
if(verbose){
pair<int, int> coord = Board::posToXY(*j);
std::cout << "other pos:" << coord.first << ", "
<< coord.second << std::endl;
std::cout << "other pos: " << coord.first + 1 << ", "
<< coord.second + 1 << std::endl;
}
//ここから深さ５の探索を行う
//ここから深さ3or5の探索を行う
DetailedMoveInfo ov; //棋譜の手以外の情報を保持する
ov = ai.detailedNegascout(i->board, -INF, INF,
h < (REPEAT_NUM >> 1) ? 3 : 5, pt);
h < (REPEAT_NUM >> 1) ? SHALLOW : DEEP, pt);
ov.score *= -1;
ov.pos = *j;
i->board.undo(*j, revPattern);
if(verbose){
// double ombsValue = ai.detailedEval(ov.board, pt).score;
std::cout << "other value:" << ov.score << std::endl;
std::cout << "other value: " << ov.score << std::endl;
// std::cout << "must be same:" << ombsValue << std::endl;
// assert(ov.score == ombsValue || ov.score == -ombsValue);
}
Expand Down Expand Up @@ -202,7 +210,7 @@ void Learner::learn(std::string filename, bool verbose)
const double cw = pt.getWeight(*itr);
//黒なら重みを大きくし、白なら小さくする
assert((1 + logistic) * (1 + logistic) != 0);
if(turn == BLACK){
if(i->board.getTurn() == BLACK){
pt.setWeight(*itr, cw + LEARNING_RATE * ACCURACY * logistic / ((1 + logistic) * (1 + logistic)));
}else{
pt.setWeight(*itr, cw - LEARNING_RATE * ACCURACY * logistic / ((1 + logistic) * (1 + logistic)));
Expand All @@ -217,7 +225,7 @@ void Learner::learn(std::string filename, bool verbose)
const double ow = pt.getWeight(*itr);
//黒なら重みを小さくし、白なら大きくする
assert((1 + logistic) * (1 + logistic) != 0);
if(turn == BLACK){
if(i->board.getTurn() == BLACK){
pt.setWeight(*itr, ow - LEARNING_RATE * ACCURACY * logistic / ((1 + logistic) * (1 + logistic))); //pow(1 + logistic, 2));
}else{
pt.setWeight(*itr, ow + LEARNING_RATE * ACCURACY * logistic / ((1 + logistic) * (1 + logistic)));
Expand All @@ -227,8 +235,8 @@ void Learner::learn(std::string filename, bool verbose)
}
cv.score = ai.detailedEval(cv.board, pt).score;
if(verbose){
std::cout << "new correct value:" << cv.score << std::endl;
std::cout << "new other value:"
std::cout << "new correct value: " << cv.score << std::endl;
std::cout << "new other value: "
<< ai.detailedEval(ov.board, pt).score << std::endl;
std::cout << std::endl;
}
Expand All @@ -241,15 +249,20 @@ void Learner::learn(std::string filename, bool verbose)
}
}

//L2正則化
// L2正則化
for(int i = 0; i < FEATURE_NUM; i++){
double w = pt.getWeight(i);
pt.setWeight(i, w - LEARNING_RATE * GAMMA * 2 * w);
}
cout << "L2 regularization done." << endl;

// randomize
Random rnd;
random_shuffle(kyokumen.begin(), kyokumen.end(), rnd);
std::cout << "Learning data randomized!" << std::endl;
}
std::cout << "Learning complete!" << std::endl;
//ファイル書き出し
// ファイル書き出し
std::ofstream ofs;
ofs.open(filename.c_str());
for(int i = 0; i < FEATURE_NUM; i++){
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14 changes: 11 additions & 3 deletions src/menu.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -195,13 +195,21 @@ void outputKifu(list<History> &hist)
void learn(const list<string> &args)
{
if(args.size() < 1){
cerr << "The output file name is required." << endl;
cerr << "The output file name (and verbose flag) is required." << endl;
return;
}
Learner ln;
list<string>::const_iterator itr = begin(args);
list<string>::const_iterator itr = begin(args);
string filename = *itr;
ln.learn(filename);
itr++;

if(args.size() == 1){
ln.learn(filename);
}else if(atoi(itr->c_str()) == LEARN_VERVOSE){
ln.learn(filename, true);
}else{
cerr << "Invalid verbose flag." << endl;
}
}

void load(AI &ai, AI &subAI, const list<string> &args)
Expand Down
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