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탐욕 알고리즘(Greedy Algorithm)
매 순간마다 최선의 선택! 오늘 알아볼 알고리즘은 ‘탐욕 알고리즘(Greedy Algorithm)’ 입니다. 알고리즘의 이름 그대로, 상당히 욕심이 많은 알고리즘 입니다. 탐욕 알고리즘이 어떤 알고리즘이냐면, 매 순간마다 최선의 선택을 하는 녀석입니다. 즉, 선택할때마다 가장 좋다고 생각되는 것을 선택해나가며 최종적인 해답을 구하는 알고리즘이라고 말할 수 있습니다. 그러나, 이 알고리즘을 설계할 때 유의할 점은 전체를 고려하는게 아니라 문제를 부분적으로 나누어, 나누어진 문제에 대한 최적의 해답을 구하므로 전체적인 최적의 해가 될 수 있는 경우가 존재합니다. 한번 예를 보아볼까요? 탐욕 알고리즘의 대표적인 문제로 거스름돈을 계산하는 문제가 있는데, 만약 거스름돈을 줄때는 최소의 동전 수로 거슬러 주며,…
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2018-02-23
Greedy Algorithms for Sparse Reinforcement Learning Christopher を読み始める。とある授業で、いくつかの論文の中から三つ論文をピックアップしてサマリーを書かなければいけないので。。
午後はほぼ採点で潰してしまった。。。ここまでの1ヶ月半、ほとんど仕事が無くて楽していたのでまぁトータルで言えばまだまだ楽している事になるだろうけれど、ここにきておよそ80人分のテスト採点（答案用紙にコードを書く問題を含む）はなかなか時間を喰う。。。
Let's do what seems the best at the moment and hope that it will be ok in the future
greedy algorithm
Interval Scheduling
Given a list of tasks, each composed of a start and an end time, return the maximum set of tasks which are compatible. Two tasks are compatible if they don't overlap.
struct comparator { bool operator()(const pair<int, int> &left, const pair<int, int> &right) { return left.second < right.second; } }; vector<pair<int, int>> IntervalScheduling(vector<pair<int, int>> &tasks) { if (tasks.size() < 1) return tasks; vector<pair<int, int>> ret; // Sort by the end times sort(tasks.begin(), tasks.end(), comparator()); // Iterate and select the immediate compatible start in a greedy manner ret.push_back(tasks[0]); for (int i = 1; i < tasks.size(); i++) if (ret[ret.size() - 1].second <= tasks[i].first) ret.push_back(tasks[i]); return ret; }
March 5/6/7/8
Wednesday: Wednesday was spent primarily focusing on my work. I had a lot of work to do, and not very much time to do it in. I woke up to Destruct lab, which actually went pretty well. After that, the entire day was spent working. For a number of hours, I stayed holed up in one of the study rooms, trying my hand at an unsolved problem called the partition problem. I don't know why I got so fixated on it, but my reasoning was that if I found a solution, my algorithm would be optimized.
Thursday: Thursday was horrible. From 8AM in the morning to 2AM the following night, I spent all of my time working or in class. I had to finish my Destruct homework, which sucked up almost all of my time, I needed to finish my game design project, and I know had a surprise math test to prepare myself for. There was not enough time in the day. I finished my homework with 20 minutes to spare, and then tried unsuccessfully to study for my math test. I still am burned out today from the amount of work I put into Thursday.
Friday: Even on Friday I couldn't catch the break I needed. I needed to finalize my game project and test it thoroughly, I needed to finish studying for math, finish the homework, and then take the test on material I hadn't even been taught yet. The teacher is completely incompetent. Finally, when four o'clock came around, I was free to go for "Spring Break." The president of my college figured that since we're a tech school and we don't have lives anyway, having our break AT THE FUCKING BEGINNING OF MARCH wouldn't be a big deal. So woo. Spring Break begins. I took a spontaneous trip to Friendly's with my roommate, and then I scrambled to catch my train to go home.
Saturday: It was my first day back home, and unsurprisingly, I spent my entire day within a total radius of maybe 50 square feet. I slept in late, ate a lot of good food, played with my niece, played a video game with her, and then I purchased a game on Steam called Octodad: Dadliest Catch. It wasn't as bad as people made it out to be, and I was finished within a couple hours. It was still a great game though. So far, I don't have very much planned for this break. Which probably isn't a bad thing, I just need to keep calm and carry on.
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Greedy Algorithm
Key characteristics about Greedy Algorithm:
Greedy choice, it needs effort and intuition to find the greedy strategy
Optimal substructure: optimal solution contains optimal solutions to subproblems
Top-down approach, make a choice and then solve a subproblem.
