
Jason
 Referenced in 62 articles
[sw06187]
 systems using the Jason platform; it reinforces learning with examples, problems, and illustrations, includes...

Approxrl
 Referenced in 29 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...

RMAX
 Referenced in 32 articles
[sw02539]
 very simple modelbased reinforcement learning algorithm which can attain nearoptimal average reward...

OpenAI Gym
 Referenced in 26 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 timeconstrained 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...

RLGlue
 Referenced in 8 articles
[sw13720]
 Glue: LanguageIndependent Software for ReinforcementLearning Experiments. RLGlue is a standard, languageindependent ... software package for reinforcementlearning experiments. The standardization provided by RLGlue facilitates code sharing...

RLlib
 Referenced in 7 articles
[sw31153]
 RLlib: Scalable Reinforcement Learning. RLlib is an opensource library for reinforcement learning that offers...

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 PythonBased Reinforcement Learning, Artificial Intelligence and Neural Network Library...

Dopamine
 Referenced in 6 articles
[sw31151]
 Dopamine: A Research Framework for Deep Reinforcement Learning. Deep reinforcement learning (deep RL) research...

Horizon
 Referenced in 5 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...

SeqGAN
 Referenced in 7 articles
[sw26534]
 generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses the generator differentiation problem...

PEORL
 Referenced in 3 articles
[sw29437]
 PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust DecisionMaking. 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 decisionmaking...

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 fullgame...

Tensorforce
 Referenced in 3 articles
[sw31158]
 Tensorforce: a TensorFlow library for applied reinforcement learning. Tensorforce is an opensource deep reinforcement ... learning framework, with an emphasis on modularized flexible library design and straightforward usability for applications ... Fullon TensorFlow models: The entire reinforcement learning logic, including control flow, is implemented...

DARTS
 Referenced in 5 articles
[sw36213]
 conventional approaches of applying evolution or reinforcement learning over a discrete and nondifferentiable search...

CARLA
 Referenced in 4 articles
[sw35046]
 model trained via reinforcement learning. The approaches are evaluated in controlled scenarios of increasing difficulty...

APES
 Referenced in 2 articles
[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 gridworld environments for reinforcement learning problems. APES equips agents with algorithms...

RLPy
 Referenced in 2 articles
[sw14300]
 RLPy: a valuefunctionbased reinforcement learning framework for education and research. RLPy ... objectoriented reinforcement learning software package with a focus on valuefunctionbased 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...

GradCAM
 Referenced in 4 articles
[sw35098]
 tasks with multimodal inputs or reinforcement learning, without any architectural changes or retraining...