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Piscifelis - AI Pathfinding Project

Piscifelis is a simple yet effective project for finding paths between two points in a coordinate system. It is designed to determine the shortest possible path—well, maybe!
This project was developed as part of the AI course at Shahed University and is licensed under MIT, making it freely accessible to learners.

Teaching Assistant:

  • Ehsan Ghafari Sadr

Implemented Pathfinding Algorithms:

This project supports several fundamental pathfinding algorithms:

How to Use

Piscifelis offers two execution modes:

  1. Manual Mode - Define obstacles, start, and target points yourself.
  2. Random Mode - Automatically generates obstacles and selects start and target points randomly.

Manual Mode Usage

  • Place obstacles anywhere on the grid; they will appear in black.
  • Click "Start Block" to select the starting point.
  • Click "Target Block" to define the target.
  • If you prefer a completely randomized setup, click "Create Block", then select "Random Grid" to let the system set obstacles and points automatically.

Algorithm Execution

  • Click "Algorithm" to view available search algorithms.
  • Select an algorithm from the list.
  • Click "Visualize" to execute the selected algorithm.
    • Visited nodes will be marked in pink.
    • Final chosen path will be shown sequentially in blue.

A* Customization

  • Choose between Manhattan or Euclidean heuristics for A* search.
  • Adjust the admissibility factor (ε) via "Settings" > "ε admissible".

Grid Size Customization

  • Default settings are optimized for standard laptop screens.
  • To modify row or column counts, access "Settings" and adjust grid parameters.

Reset and Clear Graph

  • "Reset Graph": Clears the path and algorithm-related data while preserving obstacles.
  • "Clear Graph": Removes all obstacles, paths, start, and target points.

Performance Metrics

  • View total visited nodes and algorithm execution time (ms) on-screen.

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Path Finding Project AI Course

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