Donat a n*n tauler d'escacs i el cavaller posició (x y) cada vegada que el cavaller es mou, tria un dels vuit moviments possibles de manera uniforme aleatòria (encara que la peça surti del tauler d'escacs) i es mou allà. El cavaller continua movent-se fins que hagi fet exactament k es mou o té es va traslladar el tauler d'escacs. La tasca és fer trobar el probabilitat que el cavaller restes a la tauler després que ho hagi fet aturat movent-se.
Nota: Un cavaller d'escacs pot fer vuit moviments possibles. Cada moviment és de dues cel·les en una direcció cardinal i després una cel·la en una direcció ortogonal.
Exemples:
Entrada: n = 8 x = 0 y = 0 k = 1
Sortida: 0,25
Explicació: El cavaller comença a (0 0) i després de fer un pas es trobarà dins del tauler en només 2 de les 8 posicions que són (1 2) i (2 1). Així, la probabilitat serà 2/8 = 0,25.Entrada: n = 8 x = 0 y = 0 k = 3
Sortida: 0,125Entrada: n = 4 x = 1 y = 2 k = 4
Sortida: 0,024414
Taula de continguts
- Ús de Dp de dalt a baix (memoització) - O(n*n*k) Temps i O (n*n*k) Espai
- Ús de Dp de baix a dalt (tabulació) - O (n*n*k) temps i O (n*n*k) espai
- Ús d'espai optimitzat Dp - O(n*n*k) Temps i O(n*n) Espai
Ús de Dp de dalt a baix (memoització) - O(n*n*k) Temps i O (n*n*k) Espai
C++La probabilitat que el cavaller romangui al tauler d'escacs després de k moviments és igual a la mitjana de probabilitat de cavaller a les vuit posicions anteriors després de k - 1 moviments. De la mateixa manera, la probabilitat després de k-1 moviments depèn de la mitjana de la probabilitat després de k-2 moviments. La idea és utilitzar memorització per emmagatzemar les probabilitats dels moviments anteriors i trobar la seva mitjana per calcular el resultat final.
Per fer-ho crea un Memo de matriu 3D[][][][] on nota[i][j][k] emmagatzema la probabilitat que Knight estigui a la cel·la (i j) després que k es mogui. Si k és zero, és a dir, s'arriba a l'estat inicial retorn 1 sinó explora les vuit posicions anteriors i troba la mitjana de les seves probabilitats.
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std; // recursive function to calculate // knight probability double knightProbability(int n int x int y int k vector<vector<vector<double>>> &memo){ // Base case initial probability if(k == 0) return 1.0; // check if already calculated if(memo[x][y][k] != -1) return memo[x][y][k]; vector<vector<int>> directions = {{1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2}}; memo[x][y][k] = 0; double cur = 0.0; // for every position reachable from (xy) for(auto d:directions){ int u = x + d[0]; int v = y + d[1]; // if this position lie inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += knightProbability(n u v k-1 memo) / 8.0; } return memo[x][y][k] = cur; } // Function to find the probability double findProb(int n int x int y int k) { // Initialize memo to store results vector<vector<vector<double>>> memo(n vector<vector<double>>(n vector<double> (k+1 -1))); return knightProbability(n x y k memo); } int main(){ int n = 8 x = 0 y = 0 k = 3; cout << findProb(n x y k) << endl; return 0; }
Java // Java program to find the probability of the // knight to remain inside the chessboard class GfG { // recursive function to calculate // knight probability static double knightProbability(int n int x int y int k double[][][] memo) { // Base case initial probability if (k == 0) return 1.0; // check if already calculated if (memo[x][y][k] != -1) return memo[x][y][k]; int[][] directions = {{1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2}}; memo[x][y][k] = 0; double cur = 0.0; // for every position reachable from (x y) for (int[] d : directions) { int u = x + d[0]; int v = y + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += knightProbability(n u v k - 1 memo) / 8.0; } return memo[x][y][k] = cur; } // Function to find the probability static double findProb(int n int x int y int k) { // Initialize memo to store results double[][][] memo = new double[n][n][k + 1]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { for (int m = 0; m <= k; m++) { memo[i][j][m] = -1; } } } return knightProbability(n x y k memo); } public static void main(String[] args) { int n = 8 x = 0 y = 0 k = 3; System.out.println(findProb(n x y k)); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard # recursive function to calculate # knight probability def knightProbability(n x y k memo): # Base case initial probability if k == 0: return 1.0 # check if already calculated if memo[x][y][k] != -1: return memo[x][y][k] directions = [ [1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2] ] memo[x][y][k] = 0 cur = 0.0 # for every position reachable from (x y) for d in directions: u = x + d[0] v = y + d[1] # if this position lies inside the board if 0 <= u < n and 0 <= v < n: cur += knightProbability(n u v k - 1 memo) / 8.0 memo[x][y][k] = cur return cur # Function to find the probability def findProb(n x y k): # Initialize memo to store results memo = [[[-1 for _ in range(k + 1)] for _ in range(n)] for _ in range(n)] return knightProbability(n x y k memo) n x y k = 8 0 0 3 print(findProb(n x y k))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System; class GfG { // recursive function to calculate // knight probability static double KnightProbability(int n int x int y int k double[] memo) { // Base case initial probability if (k == 0) return 1.0; // check if already calculated if (memo[x y k] != -1) return memo[x y k]; int[] directions = {{1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2}}; memo[x y k] = 0; double cur = 0.0; // for every position reachable from (x y) for (int i = 0; i < 8; i++) { int u = x + directions[i 0]; int v = y + directions[i 1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) { cur += KnightProbability(n u v k - 1 memo) / 8.0; } } return memo[x y k] = cur; } // Function to find the probability static double FindProb(int n int x int y int k) { // Initialize memo to store results double[] memo = new double[n n k + 1]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { for (int m = 0; m <= k; m++) { memo[i j m] = -1; } } } return KnightProbability(n x y k memo); } static void Main() { int n = 8 x = 0 y = 0 k = 3; Console.WriteLine(FindProb(n x y k)); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard // recursive function to calculate // knight probability function knightProbability(n x y k memo) { // Base case initial probability if (k === 0) return 1.0; // check if already calculated if (memo[x][y][k] !== -1) return memo[x][y][k]; const directions = [ [1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2] ]; memo[x][y][k] = 0; let cur = 0.0; // for every position reachable from (x y) for (let d of directions) { const u = x + d[0]; const v = y + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) { cur += knightProbability(n u v k - 1 memo) / 8.0; } } return memo[x][y][k] = cur; } // Function to find the probability function findProb(n x y k) { // Initialize memo to store results const memo = Array.from({ length: n } () => Array.from({ length: n } () => Array(k + 1).fill(-1))); return knightProbability(n x y k memo).toFixed(6); } const n = 8 x = 0 y = 0 k = 3; console.log(findProb(n x y k));
Sortida
0.125
Ús de Dp de baix a dalt (tabulació) - O (n*n*k) temps i O (n*n*k) espai
C++L'enfocament anterior es pot optimitzar mitjançant de baix a dalt tabulació que redueix l'espai addicional necessari per a la pila recursiva. La idea és mantenir un 3 D matriu dp[][][][] on dp[i][j][k] emmagatzema la probabilitat que el cavaller estigui a la cel·la (i j) després k es mou. Inicialitzar el 0è estat de dp amb valor 1 . Per a cada moviment posterior el probabilitat de cavaller serà igual a mitjana de probabilitat de anterior 8 posicions després k-1 es mou.
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std; // Function to find the probability double findProb(int n int x int y int k) { // Initialize dp to store results of each step vector<vector<vector<double>>> dp(n vector<vector<double>>(n vector<double> (k+1))); // Initialize dp for step 0 for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { dp[i][j][0] = 1.0; } } vector<vector<int>> directions = { {1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2} }; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (xy) for (auto d:directions) { int u = i + d[0]; int v = j + d[1]; // if this position lie inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += dp[u][v][move - 1] / 8.0; } // store the result dp[i][j][move] = cur; } } } // return the result return dp[x][y][k]; } int main(){ int n = 8 x = 0 y = 0 k = 3; cout << findProb(n x y k) << endl; return 0; }
Java // Java program to find the probability of the // knight to remain inside the chessboard import java.util.*; class GfG { // Function to find the probability static double findProb(int n int x int y int k) { // Initialize dp to store results of each step double[][][] dp = new double[n][n][k + 1]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { dp[i][j][0] = 1; } } int[][] directions = { {1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2} }; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (x y) for (int[] d : directions) { int u = i + d[0]; int v = j + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) { cur += dp[u][v][move - 1] / 8.0; } } // store the result dp[i][j][move] = cur; } } } // return the result return dp[x][y][k]; } public static void main(String[] args) { int n = 8 x = 0 y = 0 k = 3; System.out.println(findProb(n x y k)); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard # Function to find the probability def findProb(n x y k): # Initialize dp to store results of each step dp = [[[0 for _ in range(k + 1)] for _ in range(n)] for _ in range(n)] for i in range(n): for j in range(n): dp[i][j][0] = 1.0 directions = [[1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2]] for move in range(1 k + 1): # find probability for cell (i j) for i in range(n): for j in range(n): cur = 0.0 # for every position reachable from (x y) for d in directions: u = i + d[0] v = j + d[1] # if this position lies inside the board if 0 <= u < n and 0 <= v < n: cur += dp[u][v][move - 1] / 8.0 # store the result dp[i][j][move] = cur # return the result return dp[x][y][k] if __name__ == '__main__': n x y k = 8 0 0 3 print(findProb(n x y k))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System; class GfG { // Function to find the probability static double findProb(int n int x int y int k) { // Initialize dp to store results of each step double[] dp = new double[n n k + 1]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { dp[i j 0] = 1.0; } } int[] directions = {{1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2}}; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (x y) for (int d = 0; d < directions.GetLength(0); d++) { int u = i + directions[d 0]; int v = j + directions[d 1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) { cur += dp[u v move - 1] / 8.0; } } // store the result dp[i j move] = cur; } } } // return the result return dp[x y k]; } static void Main(string[] args) { int n = 8 x = 0 y = 0 k = 3; Console.WriteLine(findProb(n x y k)); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard // Function to find the probability function findProb(n x y k) { // Initialize dp to store results of each step let dp = Array.from({ length: n } () => Array.from({ length: n } () => Array(k + 1).fill(0)) ); // Initialize dp for step 0 for (let i = 0; i < n; ++i) { for (let j = 0; j < n; ++j) { dp[i][j][0] = 1.0; } } let directions = [[1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2]]; for (let move = 1; move <= k; move++) { // find probability for cell (i j) for (let i = 0; i < n; i++) { for (let j = 0; j < n; j++) { let cur = 0.0; // for every position reachable from (x y) for (let d of directions) { let u = i + d[0]; let v = j + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) { cur += dp[u][v][move - 1] / 8.0; } } // store the result dp[i][j][move] = cur; } } } // return the result return dp[x][y][k].toFixed(6); } let n = 8 x = 0 y = 0 k = 3; console.log(findProb(n x y k));
Sortida
0.125
Ús d'espai optimitzat Dp - O(n*n*k) Temps i O(n*n) Espai
C++L'enfocament anterior requereix només anterior estat de probabilitats per calcular el actual estat així només el anterior cal emmagatzemar la botiga. La idea és crear-ne dos matrius 2d prevMove[][] i currMove[][] on
- prevMove[i][j] emmagatzema la probabilitat que el cavaller estigui a (i j) fins al moviment anterior. S'inicialitza amb el valor 1 per a l'estat inicial.
- currMove[i][j] emmagatzema la probabilitat de l'estat actual.
Operar de manera similar a l'enfocament anterior i a final de cada iteració actualitza prevMove[][] amb el valor emmagatzemat currMove[][].
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std; // Function to find the probability double findProb(int n int x int y int k) { // dp to store results of previous move vector<vector<double>> prevMove(n vector<double>(n 1)); // dp to store results of current move vector<vector<double>> currMove(n vector<double>(n 0)); vector<vector<int>> directions = { {1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2} }; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (xy) for (auto d:directions) { int u = i + d[0]; int v = j + d[1]; // if this position lie inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += prevMove[u][v] / 8.0; } // store the result currMove[i][j] = cur; } } // update previous state prevMove = currMove; } // return the result return prevMove[x][y]; } int main(){ int n = 8 x = 0 y = 0 k = 3; cout << findProb(n x y k) << endl; return 0; }
Java // Java program to find the probability of the // knight to remain inside the chessboard class GfG { // Function to find the probability static double findProb(int n int x int y int k) { // dp to store results of previous move double[][] prevMove = new double[n][n]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { prevMove[i][j] = 1.0; } } // dp to store results of current move double[][] currMove = new double[n][n]; int[][] directions = { {1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2} }; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (xy) for (int[] d : directions) { int u = i + d[0]; int v = j + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += prevMove[u][v] / 8.0; } // store the result currMove[i][j] = cur; } } // update previous state for (int i = 0; i < n; i++) { System.arraycopy(currMove[i] 0 prevMove[i] 0 n); } } // return the result return prevMove[x][y]; } public static void main(String[] args) { int n = 8 x = 0 y = 0 k = 3; System.out.println(findProb(n x y k)); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard def findProb(n x y k): # dp to store results of previous move prevMove = [[1.0] * n for _ in range(n)] # dp to store results of current move currMove = [[0.0] * n for _ in range(n)] directions = [ [1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2] ] for move in range(1 k + 1): # find probability for cell (i j) for i in range(n): for j in range(n): cur = 0.0 # for every position reachable from (xy) for d in directions: u v = i + d[0] j + d[1] # if this position lies inside the board if 0 <= u < n and 0 <= v < n: cur += prevMove[u][v] / 8.0 # store the result currMove[i][j] = cur # update previous state prevMove = [row[:] for row in currMove] # return the result return prevMove[x][y] if __name__ == '__main__': n x y k = 8 0 0 3 print(findProb(n x y k))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System; class GfG { // Function to find the probability static double findProb(int n int x int y int k) { // dp to store results of previous move double[] prevMove = new double[n n]; for (int i = 0; i < n; i++) for (int j = 0; j < n; j++) prevMove[i j] = 1.0; // dp to store results of current move double[] currMove = new double[n n]; int[] directions = { {1 2} {2 1} {2 -1} {1 -2} {-1 -2} {-2 -1} {-2 1} {-1 2} }; for (int move = 1; move <= k; move++) { // find probability for cell (i j) for (int i = 0; i < n; ++i) { for (int j = 0; j < n; ++j) { double cur = 0.0; // for every position reachable from (xy) for (int d = 0; d < directions.GetLength(0); d++) { int u = i + directions[d 0]; int v = j + directions[d 1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += prevMove[u v] / 8.0; } // store the result currMove[i j] = cur; } } // update previous state Array.Copy(currMove prevMove n * n); } // return the result return prevMove[x y]; } static void Main() { int n = 8 x = 0 y = 0 k = 3; Console.WriteLine(findProb(n x y k)); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard function findProb(n x y k) { // dp to store results of previous move let prevMove = Array.from({ length: n } () => Array(n).fill(1.0)); // dp to store results of current move let currMove = Array.from({ length: n } () => Array(n).fill(0.0)); const directions = [ [1 2] [2 1] [2 -1] [1 -2] [-1 -2] [-2 -1] [-2 1] [-1 2] ]; for (let move = 1; move <= k; move++) { // find probability for cell (i j) for (let i = 0; i < n; i++) { for (let j = 0; j < n; j++) { let cur = 0.0; // for every position reachable from (xy) for (let d of directions) { let u = i + d[0]; let v = j + d[1]; // if this position lies inside the board if (u >= 0 && u < n && v >= 0 && v < n) cur += prevMove[u][v] / 8.0; } // store the result currMove[i][j] = cur; } } // update previous state prevMove = currMove.map(row => [...row]); } // return the result return prevMove[x][y].toFixed(6); } let n = 8 x = 0 y = 0 k = 3; console.log(findProb(n x y k));
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