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Awesome GitHub RepositoriesML Interface Adapters
Adapters that map simulation environments to standard ML API formats like Gym.
Distinct from API Adapters: Focuses on ML-specific interface normalization rather than general web API responses.
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Awesome ML Interface Adapters GitHub Repositories
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- unity-technologies/ml-agents
Unity-Technologies/ml-agents
19,494Auf GitHub ansehenThis project is a reinforcement learning toolkit and simulation-based AI trainer for creating intelligent agents within Unity simulations. It provides a multi-agent simulation framework for configuring cooperative or competitive scenarios and includes an environment wrapper that bridges simulations with standard machine learning libraries using gym-style interfaces. The system features a native cross-platform inference engine that executes trained neural network models for real-time decision making without external dependencies. It enables the acceleration of the learning process by running m
Adapts simulated environments into compatible interfaces for common machine learning libraries and gym-style APIs.
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