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TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
The main features of tensorflow/agents are: Deep Learning Ecosystems, Deep Learning Frameworks, Machine Learning Frameworks, Perception and Machine Learning, Reinforcement Learning, Reinforcement Learning and Simulation.
Projects with overlapping indexed features include: keras-rl/keras-rl — keras-rl is a reinforcement learning library that enables the training of neural agents using Keras. It serves as a… tensorforce/tensorforce — Tensorforce: a TensorFlow library for applied reinforcement learning. catalyst-team/catalyst — Accelerated deep learning R&D. deepmind/trfl — TensorFlow Reinforcement Learning. autonomio/talos — Hyperparameter Experiments with TensorFlow and Keras. cornellius-gp/gpytorch — GPyTorch is a GPU-accelerated probabilistic framework and PyTorch library for implementing scalable Gaussian process…
keras-rl is a reinforcement learning library that enables the training of neural agents using Keras. It serves as a framework for implementing deep reinforcement learning agents that interact with simulated environments to discover optimal behaviors and maximize cumulative rewards. The library provides a system for configuring, training, and managing neural network agents. It handles the interaction loop between agents and environments, allowing models to learn through direct experience and gradient-based optimization. The framework includes capabilities for model weight management, allowing
Tensorforce: a TensorFlow library for applied reinforcement learning
