CodeForces 538E Demiurges Play Again(博弈dp)

本文介绍了一种基于树形结构的动态规划算法,通过博弈论的方法解决两个玩家如何在树形路径上选择叶节点的问题。该算法适用于两人轮流进行决策的情况,并详细解释了如何通过递归方式求解玩家各自的目标——最大化和最小化所选叶节点的值。

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题意:给出一棵树,叶节点都有编号,从根节点开始,一人走一步,第一个人想要得到的叶节点最大,第二个人想最小,问怎么安排,使得第一个人得到的叶节点最大,最小。

做法:先考虑得到叶节点最大的情况。我们设dp[i]是当前人以他的走法能得到符合他的第dp[i]大数。那么假设对于第一个人,假设他的下一步第二个人可以得到第2大,第3大,第4大(3个分叉),那第一个最大可以得到下面所有数的第2大。我们可以安排最大2个数在第一个分叉,就可以了。那么这里取一个最小值即可。假设对于第二个人,想最小,那么就是对于下面分叉的儿子的dp[i]求和。因为他想得到最小的(定义的是第k大,k越大数越小)。

再看看得到叶节点最小的情况。我们可以换一下定义,把dp[i]定义为得到的第dp[i]小数,那么也类似的,第一个人想最大,那么即是求儿子的和,第二个想最小,那么即求儿子的最小值。

AC代码:

#pragma comment(linker, "/STACK:102400000,102400000")
#include<cstdio>
#include<ctype.h>
#include<algorithm>
#include<iostream>
#include<cstring>
#include<vector>
#include<cstdlib>
#include<stack>
#include<queue>
#include<set>
#include<map>
#include<cmath>
#include<ctime>
#include<string.h>
#include<string>
#include<sstream>
#include<bitset>
using namespace std;
#define ll __int64
#define ull unsigned long long
#define eps 1e-8
#define NMAX 10000000
#define MOD 1000000007
#define lson l,mid,rt<<1
#define rson mid+1,r,rt<<1|1
#define PI acos(-1)
#define mp make_pair
template<class T>
inline void scan_d(T &ret)
{
    char c;
    int flag = 0;
    ret=0;
    while(((c=getchar())<'0'||c>'9')&&c!='-');
    if(c == '-')
    {
        flag = 1;
        c = getchar();
    }
    while(c>='0'&&c<='9') ret=ret*10+(c-'0'),c=getchar();
    if(flag) ret = -ret;
}
const int maxn = 200000+10;
vector<int>v[maxn];
int dp[maxn],ge;
void dfs(int u, int fa, int dep, int flag)
{
    int sz = v[u].size();
    if(dep%2)
    {
        if(flag) dp[u] = maxn;
        else dp[u] = 0;
        for(int i = 0; i < sz; i++) if(v[u][i] != fa)
        {
            dfs(v[u][i],u,dep+1,flag);
            if(flag) dp[u] = min(dp[u],dp[v[u][i]]);
            else dp[u] += dp[v[u][i]];
        }
        if(dp[u] == maxn || dp[u] == 0)
        {
            if(flag) ge++;
            dp[u] = 1;
        }
    }
    else
    {
        if(flag) dp[u] = 0;
        else dp[u] = maxn;
        for(int i = 0; i < sz; i++) if(v[u][i] != fa)
        {
            dfs(v[u][i],u,dep+1,flag);
            if(flag) dp[u] += dp[v[u][i]];
            else dp[u] = min(dp[u],dp[v[u][i]]);
        }
        if(dp[u] == maxn || dp[u] == 0)
        {
            if(flag) ge++;
            dp[u] = 1;
        }
    }
}


int main()
{
#ifdef GLQ
    freopen("input.txt","r",stdin);
//    freopen("o.txt","w",stdout);
#endif
    int n;
    scanf("%d",&n);
    for(int i = 1; i < n; i++)
    {
        int t1,t2;
        scanf("%d%d",&t1,&t2);
        v[t1].push_back(t2);
        v[t2].push_back(t1);
    }
    int ans1,ans2;
    ge = 0;
    dfs(1,1,1,1);
    ans1 = ge-dp[1]+1;
    dfs(1,1,1,0);
    ans2 = dp[1];
    printf("%d %d\n",ans1,ans2);
    return 0;
}


### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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