snake and geneticSnakeANN

These are competitors—both implement AI-driven snake game agents using different approaches (reinforcement learning vs. genetic algorithms), solving the same problem of autonomous snake gameplay.

snake
67
Established
geneticSnakeANN
23
Experimental
Maintenance 16/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 4/25
Maturity 9/25
Community 10/25
Stars: 1,757
Forks: 553
Downloads:
Commits (30d): 2
Language: Python
License: MIT
Stars: 6
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No Package No Dependents
Stale 6m No Package No Dependents

About snake

chynl/snake

Artificial intelligence for the Snake game.

Implements three distinct solver algorithms—Hamilton cycle pathfinding for near-optimal play, greedy heuristic search, and experimental deep Q-learning—evaluated across 1000-episode trials measuring final snake length and step efficiency. Built in Python with Tkinter visualization and includes comprehensive unit tests for algorithm validation.

About geneticSnakeANN

AlbertoLanaro/geneticSnakeANN

Self learning snake with ANN-based genetic algorithm

Scores updated daily from GitHub, PyPI, and npm data. How scores work