A high-performance Python port of libtcod. Includes the libtcodpy module for backwards compatibility with older projects.

Implementation of common pathfinding algorithms

Vim plugin to suggest better movements

Simple implementation of the a-star algorithm in Python 🌟

POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.

Pathfinding visualizations with Python and Pygame

Generate Cool-Looking Mazes and Animations Illustrating the A* Pathfinding Algorithm

A very simple A* implementation in C++ callable from Python for pathfinding on a two-dimensional grid.

Improve Warehouse Productivity using Order Batching

Solving synthetic 2d path-planning problems with a convolutional neural network.

A Pytorch implementation of Generative Adversarial Network for Heuristics of Sampling-based Path Planning

Path Planning using Generative Adversarial Network (GAN)

python package for fast shortest path computation on 2D polygon or grid maps

[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

Python implementation of common pathfinding algorithms in 3D grid space

AI plays snake game using BFS (Breadth-First Search) algorithm.

A python package for planning surveys over large areas using one or more UAV (Unpersoned Aerial Vehicle).

PythonFinder: Cross Platform Search Tool for Finding Pythons

Astar algorithm with smoothed path using Fast marching method

POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.