
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...

Flappy
 Referenced in 2 articles
[sw38067]
 learning control algorithms such as Reinforcement Learning. The interface of the simulation is fully compatible ... hovering stabilization and a Deep Reinforcement Learning control policy for goaldirected maneuvering. Finally...

rllib
 Referenced in 2 articles
[sw11544]
 templatebased 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...

SBEED
 Referenced in 2 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...

LVIBRA
 Referenced in 3 articles
[sw02429]
 last years the use of online 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 learningbased dimension and delay estimator for neural networks in time ... time delay. A novel method, called reinforcement learningbased 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...

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 selfdriving 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 Qlearning, policy gradients, and Qvalue policy gradients. These ... great depth of common deep reinforcement learning machinery. We are pleased to share rlpyt, which...

OpenGraphGym
 Referenced in 1 article
[sw38102]
 OpenGraphGym: A Parallel Reinforcement Learning Framework for Graph Optimization Problems. This paper presents an open ... OpenGraphGym) to facilitate the application of reinforcement learning (RL) algorithms to address combinatorial graph optimization ... This environment incorporates a basic deep reinforcement learning method, and several graph embeddings to capture...

banditnmt
 Referenced in 1 article
[sw20941]
 banditnmt: 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...

kerasrl
 Referenced in 2 articles
[sw35087]
 some stateofthe art deep reinforcement learning algorithms in Python and seamlessly integrates with...

Stable Baselines
 Referenced in 2 articles
[sw34408]
 improved implementations of reinforcement learning algorithms based on OpenAI Baselines...

ProMP
 Referenced in 2 articles
[sw34914]
 Policy Search. Credit assignment in Metareinforcement learning (MetaRL) is still poorly understood. Existing...