Skip to content

Knight On Chess Board

Logical Breakdown

  • [ ] Subproblem Identification:
  • [ ] Optimal Substructure:
  • [ ] Constraint Handling: (e.g., Modulo \(10^9 + 7\))
  • [ ] Optimization: (Matrix Exponentiation if 'A' is huge)

Mathematical Rigor

State Definition

Let \(dp[i]\) be the state for the \(i\)-th subproblem.

Recurrence Relation

\[ dp[i] = ... \]

Visualization

graph TD A["Current State"] --> B["Previous State 1"] A --> C["Previous State 2"]

Complexity Analysis

Approach Time Complexity Space Complexity
Iterative DP \(O(N)\) \(O(1)\)

Code Reference

package com.dsa.graphs;

import java.util.*;

/* * ============================================================================================ * PROBLEM: Knight On Chess Board * ============================================================================================ * * --------------------- * 1. Problem Description * --------------------- * Given a chessboard of size A x B. Find the minimum steps a Knight takes to move from * source (C, D) to destination (E, F). * - A Knight moves in an "L" shape: 2 steps in one cardinal direction and 1 step * perpendicularly. * - Return -1 if the destination is unreachable. * * --------------------- * 2. Logical Breakdown & Mathematical Formulation * --------------------- * This is a Shortest Path problem in an unweighted grid, which is best solved using BFS. * * Step 1: Define Knight Moves * A knight has 8 possible moves from (x, y): * (x+2, y+1), (x+2, y-1), (x-2, y+1), (x-2, y-1), * (x+1, y+2), (x+1, y-2), (x-1, y+2), (x-1, y-2) * * Step 2: BFS Implementation * 1. Initialization: * - Use a 2D visited array or dist array initialized to -1. * - Convert 1-based coordinates to 0-based: (C-1, D-1) and (E-1, F-1). * - Push the starting point into a Queue and set dist[start] = 0. * 2. Traversal: * - While Queue is not empty: * - Pop current (currX, currY). * - If current == destination, return dist[currX][currY]. * - Explore all 8 knight moves. * - For each move (nextX, nextY): * - If it's within bounds (0 <= nextX < A, 0 <= nextY < B) and NOT visited: * - Set dist[nextX][nextY] = dist[currX][currY] + 1. * - Enqueue (nextX, nextY). * * --------------------- * 3. Constraints & Complexity Analysis * --------------------- * Time Complexity: O(A * B) * - In the worst case, every cell of the board is visited once. * Space Complexity: O(A * B) * - To store the distance/visited matrix and the queue. * * ============================================================================================ / public class KnightOnChessBoard { public int solve(int A) { // TODO: Implement solution return 0; }

public int knight(int i, int i1, int i2, int i3, int i4, int i5) {
    return 1;
}

}