• Jason

  • Referenced in 57 articles [sw06187]
  • systems using the Jason platform; it reinforces learning with examples, problems, and illustrations, includes...
  • Approxrl

  • Referenced in 26 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...
  • R-MAX

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

  • Referenced in 12 articles [sw15330]
  • OpenAI Gym is a toolkit for reinforcement learning research. It includes a growing collection...
  • TEXPLORE

  • Referenced in 7 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...
  • 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...
  • PyBrain

  • Referenced in 9 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...
  • RLlib

  • Referenced in 4 articles [sw31153]
  • RLlib: Scalable Reinforcement Learning. RLlib is an open-source library for reinforcement learning that offers...
  • ELF

  • Referenced in 4 articles [sw26533]
  • Lightweight and Flexible platform for fundamental reinforcement learning research. Using ELF, we implement a highly ... notebook. When coupled with modern reinforcement learning methods, the system can train a full-game...
  • Dopamine

  • Referenced in 3 articles [sw31151]
  • Dopamine: A Research Framework for Deep Reinforcement Learning. Deep reinforcement learning (deep RL) research...
  • PEORL

  • Referenced in 2 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...
  • RLPy

  • Referenced in 2 articles [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...
  • RLgraph

  • Referenced in 2 articles [sw31155]
  • RLgraph: Modular Computation Graphs for Deep Reinforcement Learning. Reinforcement learning (RL) tasks are challenging ... library for designing and executing reinforcement learning tasks in both static graph and define...
  • SeqGAN

  • Referenced in 4 articles [sw26534]
  • generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses the generator differentiation problem...
  • Tensorforce

  • Referenced in 2 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...
  • Horizon

  • Referenced in 2 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...
  • rllib

  • Referenced in 2 articles [sw11544]
  • template-based reinforcement learning library: fitting the code to the mathematics. This paper introduces ... good fit between the mathematics of reinforcement learning and their implementation in a library...
  • 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...
  • APES

  • Referenced in 1 article [sw26484]
  • APES: a Python toolbox for simulating reinforcement learning environments. Assisted by neural networks, reinforcement learning ... essential component in any reinforcement learning problem. The environment simulates the dynamics of the agents ... create 2D grid-world environments for reinforcement learning problems. APES equips agents with algorithms...
  • 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...