README.md

1. Class Structure

The algorithm is encapsulated within the Search_Student class, designed to handle the search process. It contains essential properties and methods for initializing, starting, and iterating through the search.

2. Initialization

• Constructor:
  • Initializes the search configuration, grid, start and goal positions, cost, and other necessary variables.

3. Start Search

• startSearch(sx, sy, gx, gy):
  • Initiates the search process by setting the start and goal positions.
  • Resets open and closed lists and creates the root node representing the start state.
  • Marks the search as in progress.

4. Search Iteration

• searchIteration():
  • Performs one iteration of the search process.
  • Expands nodes based on the selected search strategy (BFS or DFS).
  • Checks for the goal state, updates path, and sets the cost if the goal is found.
  • Manages open and closed lists to keep track of visited nodes.

5. Node Expansion

• expand(node):
  • Expands a given node by generating child nodes based on legal actions.
  • Child nodes are added to the open list for future exploration.

6. Iterative Deepening Depth-First Search (IDDFS)

• searchIterationIDDFS():
  • Handles search iterations specifically for Iterative Deepening Depth-First Search.
  • Increments the search depth with each iteration.
  • Expands nodes only if their depth is within the current depth limit.
  • Manages cutoff conditions when the depth limit is reached.

7. Legal Actions and State Checking

• isLegalAction(x, y, action):
  • Checks if a given action is legal from a specified position on the grid.
  • Ensures that the new state is within the grid boundaries and maintains consistency with the grid values.

8. Result and Path Construction

• foundGoal(node):

  • Constructs the path when the goal state is found.
  • Sets the cost based on the length of the path.

• didNotFindGoal():

  • Handles situations where the goal state is not found.
  • Marks the search as not in progress, resets variables, and sets the cost to -1.

9. CloseList Optimization

• CloseList class:
  • Implements a 2D array for optimizing the tracking of visited points.
  • Saves and looks up points efficiently.
  • Allows resetting and retrieving all points.

10. Usage and Configuration

• Usage section in README:
  • Provides instructions on how to use the algorithm.
  • Explains the configuration options, including legal actions, action costs, and search strategy.

11. Media Section

Breadth-First Search (BFS)

Image: BFS Visualization

Video: BFS Algorithm in Action

Depth-First Search (DFS)

Image: DFS Visualization

Video: DFS Algorithm in Action

Iterative Deepening Depth-First Search (ID-DFS)

Image: ID-DFS Visualization

Video: ID-DFS Algorithm in Action

These main ideas collectively form a basic framework for a grid-based search algorithm that can be applied to various problems. The specific search strategy (BFS, DFS, IDDFS) and the grid-related details are crucial aspects of the algorithm's functionality.