What are the main features of tensorflow/agents?

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.

What are some open-source alternatives to tensorflow/agents?

Open-source alternatives to tensorflow/agents 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…

Agents - train reinforcement learning models

Name: tensorflow/agents
Author: tensorflow

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

Features

Deep Learning Ecosystems - Reinforcement learning library for TensorFlow.
Deep Learning Frameworks - Reinforcement learning library for TensorFlow.
Machine Learning Frameworks - Scalable library for reinforcement learning and bandits.
Perception and Machine Learning - Scalable library for reinforcement learning and bandits.
Reinforcement Learning - Efficient batched reinforcement learning library for TensorFlow.
Reinforcement Learning and Simulation - Scalable library for reinforcement learning and contextual bandits.

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

Features

Deep Learning Ecosystems - Reinforcement learning library for TensorFlow.
Deep Learning Frameworks - Reinforcement learning library for TensorFlow.
Machine Learning Frameworks - Scalable library for reinforcement learning and bandits.
Perception and Machine Learning - Scalable library for reinforcement learning and bandits.
Reinforcement Learning - Efficient batched reinforcement learning library for TensorFlow.
Reinforcement Learning and Simulation - Scalable library for reinforcement learning and contextual bandits.

deepmind/trfl

3,135View on GitHub

TensorFlow Reinforcement Learning

keras-rl/keras-rl

5,551View on GitHub

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

catalyst-team/catalyst

3,376View on GitHub

Accelerated deep learning R&D

tensorforce/tensorforce

3,307View on GitHub

Tensorforce: a TensorFlow library for applied reinforcement learning

deepmind/trfl

3,135View on GitHub

TensorFlow Reinforcement Learning

keras-rl/keras-rl

5,551View on GitHub

catalyst-team/catalyst

3,376View on GitHub

Accelerated deep learning R&D

tensorforce/tensorforce

3,307View on GitHub

Tensorforce: a TensorFlow library for applied reinforcement learning

tensorflowagents

Agents

Features

Star history

tensorflowagents

Agents

Features

Open-source alternatives to Agents

deepmind/trfl

keras-rl/keras-rl

catalyst-team/catalyst

tensorforce/tensorforce

Frequently asked questions

Star history

Open-source alternatives to Agents

deepmind/trfl

keras-rl/keras-rl

catalyst-team/catalyst

tensorforce/tensorforce

Frequently asked questions