Probabilitat que Knight romangui a l'escacs
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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 ));
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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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0.125Crea un qüestionari
