Data Structures and Algorithms in Python | 32. Backtracking, N queens - Part B by Abraham | Learn Smarter
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32. Backtracking, N queens - Part B

The chapter explores the N-Queens problem, detailing how to effectively represent and solve this problem using a backtracking algorithm. It highlights the need for efficient use of space in tracking attacked squares and demonstrates strategies for determining safe positions for queens on a chessboard. The implementation in Python showcases the use of dictionaries for a more compact and efficient representation of board states and queen placements.

Sections

  • 32.1

    Representation Of Attacks In N-Queens Problem

    This section discusses how to efficiently represent attacks in the N-Queens problem using a linear array approach, optimizing memory usage.

    Learning Practice

  • 32.1.1

    Attack Representation Strategy

    This section discusses the representation of attacks on a chessboard by queens, specifically focusing on space-efficient strategies that utilize linear arrays to determine attacks on squares.

    Learning Practice

  • 32.1.2

    Diagonal Representation

    This section explains how to represent the attack zones of queens in the N-Queens problem using diagonal and linear arrays.

    Learning Practice

  • 32.1.3

    Confirming Squares Under Attack

    This section discusses how to manage a queen's attack in chess using an efficient representation for tracking attacked squares.

    Learning Practice

  • 32.2

    Space Optimization Techniques

    This section discusses the strategies for optimizing space in the context of the N-Queens problem, focusing on efficient representation and tracking of attacked squares.

    Learning Practice

  • 32.2.1

    Using Arrays For Rows, Columns, And Diagonals

    This section discusses how to efficiently use arrays to track attack patterns of queens on a chessboard, focusing on optimizing space utilization.

    Learning Practice

  • 32.2.2

    Implementation Details

    The section covers how to efficiently implement the attack representation for the N-Queens problem, focusing on optimizing space while ensuring accurate tracking of queen positions and attacks.

    Learning Practice

  • 32.3

    Python Implementation And Functions

    This section discusses a Python implementation of the N-Queens problem, focusing on how to effectively manage the attacking and placing of queens using arrays and dictionaries.

    Learning Practice

  • 32.3.1

    Place Queen Function

    This section discusses the implementation of the Queen placement function for solving the N-Queens problem, focusing on attack tracking and optimization.

    Learning Practice

  • 32.3.2

    Board Initialization

    This section discusses the initialization of the board for the N-Queens problem, focusing on the representation of attacked positions and efficient space usage.

    Learning Practice

  • 32.3.3

    Checking Free Square

    This section discusses an efficient approach to check if a square in a board is free from attacks in the N-Queens problem using linear space.

    Learning Practice

  • 32.3.4

    Adding And Undoing Queens

    This section discusses how to efficiently manage the placement and removal of queens in an N-Queens problem using an attack array.

    Learning Practice

  • 32.4

    Finding All Solutions

    This section discusses an optimized data structure approach to track the positions of queens in the N-Queens problem, focusing on reducing space complexity while allowing efficient queen placement.

    Learning Practice

  • 32.4.1

    Simplified Search Process

    This section discusses the optimization of the search process in a queen placement algorithm by using a linear representation to track attacks on the board.

    Learning Practice

  • 32.4.2

    Code Adjustments For Printing All Solutions

    This section discusses adjustments in coding techniques needed to properly track the positions of queens in the n-queens problem to efficiently print all solutions.

    Learning Practice

References

Chapter 32 part-B.pdf

Class Notes

Memorization

What we have learnt

  • The N-Queens problem involv...
  • Efficient representation of...
  • Backtracking is a key algor...

Final Test

Revision Tests