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keras-rl avatar

keras-rl/keras-rl

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5,551 stars·1,347 forks·Python·MIT·13 vueskeras-rl.readthedocs.io↗

Keras Rl

keras-rl est une bibliothèque d'apprentissage par renforcement qui permet l'entraînement d'agents neuronaux en utilisant Keras. Elle sert de framework pour implémenter des agents de deep reinforcement learning qui interagissent avec des environnements simulés pour découvrir des comportements optimaux et maximiser les récompenses cumulées.

La bibliothèque fournit un système pour configurer, entraîner et gérer des agents de réseaux de neurones. Elle gère la boucle d'interaction entre les agents et les environnements, permettant aux modèles d'apprendre par expérience directe et optimisation basée sur le gradient.

Le framework inclut des capacités de gestion des poids des modèles, permettant aux utilisateurs de sauvegarder et de restaurer les états appris des agents entraînés pour préserver la progression ou les déployer pour évaluation.

Features

  • Deep Reinforcement Learning Implementations - A comprehensive framework for implementing deep reinforcement learning agents using neural networks.
  • Agent-Environment Interaction Loops - Provides the core interaction loop that generates training data through agent-environment experience.
  • Keras Model Implementations - Utilizes the Keras API to define and train the neural networks that serve as agent function approximators.
  • RL Agent Managers - Manages the full lifecycle of neural agents, from configuration and training to weight saving.
  • Reinforcement Learning - A specialized library for implementing reinforcement learning agents using Keras neural networks.
  • Reinforcement Learning Training - Provides a general framework for training agents in simulation environments using stochastic gradient descent.
  • RL Agent Implementation Frameworks - Provides the structural support and abstractions needed to implement reinforcement learning agents.
  • Simulation Environment Interfacing - Connects deep learning models to environments where they can take actions and receive rewards.
  • Agent Training Workflows - Coordinates the configuration and execution of learning algorithms to teach agents optimal behaviors.
  • Model Weight Management - Provides utilities for storing and loading model weights to preserve agent progress.
  • Experience-Driven Weight Updates - Updates neural network weights based on the outcomes of actions taken within a simulated environment.
  • Agent Training Configurations - Prepares agents for training by configuring the necessary optimizers and evaluation metrics.
  • Training Parameter Configurations - Provides a system to configure optimizers and performance metrics independently from the learning algorithm logic.
  • Model State Serialization - Enables saving and restoring of neural network weights and optimizer states to preserve training progress.
  • Deep Learning Ecosystems - Deep reinforcement learning for Keras.
  • Deep Learning Frameworks - Deep reinforcement learning for Keras.
  • Frameworks d'apprentissage automatique - Reinforcement learning for Keras.
  • Reinforcement Learning - Deep reinforcement learning for Keras.

Historique des stars

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Voir les 30 alternatives à Keras Rl→

Questions fréquentes

Que fait keras-rl/keras-rl ?

keras-rl est une bibliothèque d'apprentissage par renforcement qui permet l'entraînement d'agents neuronaux en utilisant Keras. Elle sert de framework pour implémenter des agents de deep reinforcement learning qui interagissent avec des environnements simulés pour découvrir des comportements optimaux et maximiser les récompenses cumulées.

Quelles sont les fonctionnalités principales de keras-rl/keras-rl ?

Les fonctionnalités principales de keras-rl/keras-rl sont : Deep Reinforcement Learning Implementations, Agent-Environment Interaction Loops, Keras Model Implementations, RL Agent Managers, Reinforcement Learning, Reinforcement Learning Training, RL Agent Implementation Frameworks, Simulation Environment Interfacing.

Quelles sont les alternatives open-source à keras-rl/keras-rl ?

Les alternatives open-source à keras-rl/keras-rl incluent : tensorpack/tensorpack — Tensorpack is a high-level TensorFlow neural network framework and research library designed for building and training… tensorlayer/tensorlayer — TensorLayer is a backend-agnostic tensor library and deep learning framework designed for building neural network… tflearn/tflearn — tflearn is a deep learning framework and high-level API wrapper for TensorFlow. It provides a toolkit for designing… deepmind/sonnet — Sonnet is a modular machine learning framework and TensorFlow library used for building, training, and managing deep… tensorflow/agents — TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning. deepmind/trfl — TensorFlow Reinforcement Learning.