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Probabilidad de que el Caballo permanezca en el tablero

Pruébalo en GfG Practice ' title=

dado un n*n tablero de ajedrez y el caballero posición (x y) Cada vez que el caballo debe moverse, elige uno de los ocho movimientos posibles de manera uniforme en aleatorio (incluso si la pieza se saliera del tablero) y se mueve allá. el caballero continúa moviéndose hasta que haya hecho exactamente k se mueve o tiene se mudó el tablero de ajedrez. La tarea es encontrar el probabilidad que el caballero restos en el junta después de que haya interrumpido emocionante.

Nota: Un caballo de ajedrez puede realizar ocho movimientos posibles. Cada movimiento consta de dos celdas en dirección cardinal y luego una celda en dirección ortogonal.

Ejemplos:  



Aporte: norte = 8 x = 0 y = 0 k = 1
Producción: 0,25
Explicación: El caballo comienza en (0 0) y luego de dar un paso se ubicará dentro del tablero en solo 2 de 8 posiciones que son (1 2) y (2 1). Por tanto, la probabilidad será 2/8 = 0,25.

Aporte : norte = 8 x = 0 y = 0 k = 3
Producción: 0,125

Aporte: norte = 4 x = 1 y = 2 k = 4
Producción: 0.024414

Tabla de contenido

Uso de Dp de arriba hacia abajo (memorización): tiempo O(n*n*k) y espacio O(n*n*k)

La probabilidad de que el caballo permanezca en el tablero de ajedrez después de k movimientos es igual al promedio de la probabilidad de que el caballo permanezca en las ocho posiciones anteriores después de k - 1 movimientos. De manera similar, la probabilidad después de k-1 movimientos depende del promedio de la probabilidad después de k-2 movimientos. La idea es utilizar memorización para almacenar las probabilidades de movimientos anteriores y encontrar su promedio para calcular el resultado final.
Para ello cree un Nota de matriz 3D[][][] dónde nota[i][j][k] almacena la probabilidad de que el caballero esté en la celda (i j) después de k movimientos. Si k es cero, es decir, se alcanza el estado inicial regresar 1 De lo contrario, explore las ocho posiciones anteriores y encuentre el promedio de sus probabilidades.

C++ 
// 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));

Producción 
0.125

Uso de Dp ascendente (tabulación): tiempo O(n*n*k) y espacio O(n*n*k)

El enfoque anterior se puede optimizar usando de abajo hacia arriba tabulación que reduce el espacio adicional requerido para la pila recursiva. La idea es mantener un 3 D matriz dp[][][] dónde dp[i][j][k] almacena la probabilidad de que el caballero esté en la celda (yo j) después k se mueve. Inicializar el 0º estado de dp con valor 1 . Para cada movimiento posterior, el probabilidad de caballero será igual a promedio de probabilidad de anterior 8 posiciones después k-1 se mueve.

C++ 
// 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));

Producción 
0.125

Uso de Dp optimizado para el espacio: tiempo O(n*n*k) y espacio O(n*n)

El enfoque anterior requiere solo anterior estado de probabilidades para calcular el actual estado así solo el anterior la tienda necesita ser almacenada. La idea es crear dos. Matrices 2d anteriorMove[][] y movimiento actual[][] dónde

  • prevMove[i][j] almacena la probabilidad de que el caballo esté en (i j) hasta el movimiento anterior. Se inicializa con el valor 1 para el estado inicial.
  • currMove[i][j] almacena la probabilidad del estado actual.

Opere de manera similar al enfoque anterior y en fin de cada iteración actualizar movimiento anterior[][] con valor almacenado en movimiento actual[][].

C++ 
// 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));

Producción 
0.125
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