snake and snake-reinforcement-learning

These are competitors offering alternative AI approaches to the same problem—one implements neural networks with reinforcement learning while the other uses genetic algorithms—allowing developers to choose based on preferred machine learning methodology.

snake
67
Established
Maintenance 16/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 6/25
Maturity 9/25
Community 16/25
Stars: 1,757
Forks: 553
Downloads:
Commits (30d): 2
Language: Python
License: MIT
Stars: 23
Forks: 7
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
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 snake-reinforcement-learning

arthurdjn/snake-reinforcement-learning

Genetic Algorithm and Neural Network for the snake game.

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