Strategy Game(模拟)

本文介绍了一种通过编程解决策略游戏中确定最终胜者的算法。在该策略游戏中,多个玩家轮流进行游戏并获得胜利点数,最终胜者为累积胜利点数最多且最后出手的玩家。文章提供了完整的代码实现,采用C++语言。

Strategy Game(模拟)

题目描述

A strategy game with J players is played around a table. Players are identified by numbers from 1 to J and will play a total of R rounds.
At each round each player will play once, in the order of their identifiers; that is, player 1 will play first, player 2 will play second, and so on. Once player J plays, the round is complete, and a next round starts.
A player earns a certain amount of Victory Points every time she or he plays. After all rounds are finished the total points of each player is computed as the sum of Victory Points the player earned on
each round. The winner is the player with the maximum number of points; in case of a tie the winner is the player who earned the maximum number of points and played last.
Given the number of players, the number of rounds and a list describing the Victory Points in the order they were obtained, you must determine which player is the winner.

输入

The input contains several test cases. In each test case, the first line contains two integers J and R,respectively the number of players and the number turns (1 ≤ J, R ≤ 500). The second line contains
J ∗ R integers, representing the Victory Points earned by each player in each turn, in the order they happened. The Victory Points obtained in each turn will be always integer numbers between 0 and 100, inclusive.

输出

For each test case in the input, your program must produce one single line, containing the integer representing the winner.

样例输入 

3 3
1 1 1 1 2 2 2 3 3
2 3
0 0 1 0 2 0

样例输出 

3
1

思路:入门题,比赛时看到是英文题就没注意,后来快结束的时候读了一下题,早知道就先开这道...附上AC代码

#include<bits/stdc++.h>
using namespace std;

int main()
{
	int j = 0; int r = 0;
	
	while(cin >> j >> r)
	{
		vector<int> score(j, 0);
		for(int k = 0; k < r; ++k)
		{
			for(int i = 0; i < j; ++i)
			{
				int temp = 0;
				cin >> temp;
				score[i] += temp;
			}
		}
		
		int max = 0;
		int winner = 0;
		
		for(int i = 0; i < j; ++i)
		{
			if(score[i] >= max)
			{
				max = score[i];
				winner = i + 1;
			}
		}
	
		cout << winner << endl;
	}
	
	
	return 0;
}

 

【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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