• Jason

  • Referenced in 65 articles [sw06187]
  • systems using the Jason platform; it reinforces learning with examples, problems, and illustrations, includes...
  • Approxrl

  • Referenced in 32 articles [sw14312]
  • implementations of a number of approximate reinforcement learning (RL) and dynamic programming (DP) algorithms. Notably ... Schutter, and D. Ernst, Reinforcement Learning and Dynamic Programming Using Function Approximators, CRC Press, Automation...
  • OpenAI Gym

  • Referenced in 43 articles [sw15330]
  • OpenAI Gym is a toolkit for reinforcement learning research. It includes a growing collection...
  • R-MAX

  • Referenced in 32 articles [sw02539]
  • very simple model-based reinforcement learning algorithm which can attain near-optimal average reward...
  • Grad-CAM

  • Referenced in 21 articles [sw35098]
  • tasks with multimodal inputs or reinforcement learning, without any architectural changes or re-training...
  • TEXPLORE

  • Referenced in 9 articles [sw13721]
  • TEXPLORE: temporal difference reinforcement learning for robots and time-constrained domains This book presents ... develops new reinforcement learning methods that enable fast and robust learning on robots in real ... that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential...
  • RLlib

  • Referenced in 9 articles [sw31153]
  • RLlib: Scalable Reinforcement Learning. RLlib is an open-source library for reinforcement learning that offers...
  • IMPALA

  • Referenced in 9 articles [sw41064]
  • collection of tasks using a single reinforcement learning agent with a single set of parameters ... high throughput by combining decoupled acting and learning with a novel off-policy correction method ... effectiveness of IMPALA for multi-task reinforcement learning on DMLab...
  • Dopamine

  • Referenced in 8 articles [sw31151]
  • Dopamine: A Research Framework for Deep Reinforcement Learning. Deep reinforcement learning (deep RL) research...
  • RL-Glue

  • Referenced in 8 articles [sw13720]
  • Glue: Language-Independent Software for Reinforcement-Learning Experiments. RL-Glue is a standard, language-independent ... software package for reinforcement-learning experiments. The standardization provided by RL-Glue facilitates code sharing...
  • Stable Baselines

  • Referenced in 11 articles [sw34408]
  • improved implementations of reinforcement learning algorithms based on OpenAI Baselines...
  • DARTS

  • Referenced in 11 articles [sw36213]
  • conventional approaches of applying evolution or reinforcement learning over a discrete and non-differentiable search...
  • PyBrain

  • Referenced in 10 articles [sw12670]
  • still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test ... PyBrain is short for Python-Based Reinforcement Learning, Artificial Intelligence and Neural Network Library...
  • Horizon

  • Referenced in 6 articles [sw31157]
  • Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform. In this paper we present Horizon ... Facebook’s open source applied reinforcement learning (RL) platform. Horizon ... showcase and describe real examples where reinforcement learning models trained with Horizon significantly outperformed...
  • PEORL

  • Referenced in 5 articles [sw29437]
  • PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making. Reinforcement learning ... used to build intelligent autonomous agents. Reinforcement learning relies on learning from interactions with real ... that integrates symbolic planning with hierarchical reinforcement learning (HRL) to cope with decision-making...
  • SeqGAN

  • Referenced in 9 articles [sw26534]
  • generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses the generator differentiation problem...
  • SBEED

  • Referenced in 6 articles [sw34727]
  • SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. When function approximation is used, solving ... remained a major open problem in reinforcement learning for decades. The fundamental difficulty is that...
  • Tensorforce

  • Referenced in 4 articles [sw31158]
  • Tensorforce: a TensorFlow library for applied reinforcement learning. Tensorforce is an open-source deep reinforcement ... learning framework, with an emphasis on modularized flexible library design and straightforward usability for applications ... Full-on TensorFlow models: The entire reinforcement learning logic, including control flow, is implemented...
  • Ray

  • Referenced in 7 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...
  • Pybullet

  • Referenced in 7 articles [sw35090]
  • physics simulation, robotics and deep reinforcement learning based on the Bullet Physics SDK. With pybullet...