wagenaartje/agario-ai
Neural agents learn to play in an agario-like environment with Neataptic
This project helps demonstrate how neural networks can learn to play the game Agar.io, mimicking human-like strategies. It takes game environment settings and parameters for genetic algorithms as input, then simulates neural agents playing the game and evolving over generations. It's designed for anyone interested in observing artificial intelligence learn complex behaviors in a game setting.
No commits in the last 6 months.
Use this if you want to see how AI can learn survival and competitive strategies in a game environment through simulated evolution.
Not ideal if you're looking for a tool to develop or train AI for real-world applications or other game genres, as it's specifically tailored for an Agar.io-like scenario.
Stars
58
Forks
21
Language
JavaScript
License
MIT
Category
Last pushed
Dec 04, 2021
Commits (30d)
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