ml-agents-dodgeball-env and ml-agents-snowball-fight
Both are distinct Unity ML-Agents environments, making them competitors as users would likely choose one over the other based on their specific multi-agent simulation needs.
About ml-agents-dodgeball-env
Unity-Technologies/ml-agents-dodgeball-env
Showcase environment for ML-Agents
This environment helps game developers or AI researchers create and test complex AI behaviors for cooperative and adversarial team-based games. You provide game environments and player actions, and it outputs trained AI agents capable of playing dodgeball-style games. Game AI designers and researchers focused on multi-agent learning would use this.
About ml-agents-snowball-fight
simoninithomas/ml-agents-snowball-fight
A multi-agent environment using Unity ML-Agents Toolkit
This environment provides a simulated 2 vs 2 snowball fight game where four AI agents compete. It helps developers create and train machine learning models for cooperative and adversarial multi-agent behaviors. Input involves configuring the game environment and agent reward functions, and the output is trained AI agents capable of playing the game effectively. This is for AI/ML researchers and game AI developers.
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