• RALF

  • Referenced in 2 articles [sw33955]
  • RALF - Reinforced Active Learning Formulation. RALF is the framework used in [1] and part ... This framework combines active learning and reinforcement learning to enable a time-varying trade...
  • L-VIBRA

  • Referenced in 3 articles [sw02429]
  • last years the use of on-line learning approaches to achieve coordination has attracted ... this work is to use a Reinforcement Learning approach in the job of learning...
  • MazeBase

  • Referenced in 3 articles [sw26504]
  • games, designed as a sandbox for machine learning approaches to reasoning and planning. Within ... network, memory network) are deployed via reinforcement learning on these games, with and without...
  • RLDDE

  • Referenced in 3 articles [sw35866]
  • RLDDE: A novel reinforcement learning-based dimension and delay estimator for neural networks in time ... time delay. A novel method, called reinforcement learning-based dimension and delay estimator (RLDDE...
  • mdp

  • Referenced in 3 articles [sw21994]
  • Norvig. It does not implement reinforcement learning or POMDPs. For a very similar package...
  • Ray

  • Referenced in 3 articles [sw28740]
  • will continuously interact with the environment and learn from these interactions. These applications impose ... existing specialized systems for several challenging reinforcement learning applications...
  • Grad-CAM

  • Referenced in 3 articles [sw35098]
  • tasks with multimodal inputs or reinforcement learning, without any architectural changes or re-training...
  • OR-Gym

  • Referenced in 1 article [sw34774]
  • Reinforcement Learning Library for Operations Research Problem. Reinforcement learning (RL) has been widely applied ... open-source library for developing reinforcement learning algorithms to address operations research problems. In this ... paper, we apply reinforcement learning to the knapsack, multi-dimensional bin packing, multi-echelon supply...
  • RLPy

  • Referenced in 1 article [sw14300]
  • RLPy: a value-function-based reinforcement learning framework for education and research. RLPy ... object-oriented reinforcement learning software package with a focus on value-function-based methods using ... functions), facilitating recently increased specialization in reinforcement learning. RLPy is written in Python to allow ... properties allow users to compare various reinforcement learning algorithms with little effort...
  • Tianshou

  • Referenced in 1 article [sw35091]
  • Tianshou is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries ... pythonic API for building the deep reinforcement learning agent with the least number of lines...
  • Metacar

  • Referenced in 1 article [sw27153]
  • Metacar: A reinforcement learning environment for self-driving cars in the browser. Metacar ... reinforcement learning environment for autonomous vehicles running in the browser. The project aims ... reinforcement learning be more accessible to everyone through solving fun problems. Metacar comes with...
  • rlpyt

  • Referenced in 1 article [sw31152]
  • Research Code Base for Deep Reinforcement Learning in PyTorch. Since the recent advent of deep ... reinforcement learning for game play and simulated robotic control, a multitude of new algorithms have ... categorized into three families: deep Q-learning, policy gradients, and Q-value policy gradients. These ... great depth of common deep reinforcement learning machinery. We are pleased to share rlpyt, which...
  • bandit-nmt

  • Referenced in 1 article [sw20941]
  • bandit-nmt: Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback. Machine translation ... natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings ... generated reference translations. We describe a reinforcement learning algorithm that improves neural machine translation systems...
  • Piqle

  • Referenced in 2 articles [sw14313]
  • fast design, prototyping and test of reinforcement learning experiments (RL). By clearly separating algorithms...
  • keras-rl

  • Referenced in 2 articles [sw35087]
  • some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with...
  • ProMP

  • Referenced in 2 articles [sw34914]
  • Policy Search. Credit assignment in Meta-reinforcement learning (Meta-RL) is still poorly understood. Existing...
  • MDPtoolbox

  • Referenced in 2 articles [sw22705]
  • also proposes some functions related to Reinforcement Learning...
  • Pybullet

  • Referenced in 2 articles [sw35090]
  • physics simulation, robotics and deep reinforcement learning based on the Bullet Physics SDK. With pybullet...
  • Baselines

  • Referenced in 2 articles [sw34812]
  • high-quality implementations of reinforcement learning algorithms. These algorithms will make it easier...
  • MolGAN

  • Referenced in 2 articles [sw36059]
  • combine our approach with a reinforcement learning objective to encourage the generation of molecules with...