SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 13951–14000 of 15113 papers

TitleStatusHype
Efficient Exploration through Bayesian Deep Q-NetworksCode0
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning—0
Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control—0
Evolved Policy GradientsCode0
A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems—0
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement LearningCode0
Reinforcement Learning with Wasserstein Distance Regularisation, with Applications to Multipolicy Learning—0
Reinforcement Learning for Solving the Vehicle Routing ProblemCode0
M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search—0
Efficient Model-Based Deep Reinforcement Learning with Variational State TabulationCode0
Sample Efficient Deep Reinforcement Learning for Dialogue Systems with Large Action Spaces—0
More Robust Doubly Robust Off-policy Evaluation—0
Beyond the One Step Greedy Approach in Reinforcement Learning—0
Balancing Two-Player Stochastic Games with Soft Q-Learning—0
Learning and Querying Fast Generative Models for Reinforcement Learning—0
Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis—0
A Critical Investigation of Deep Reinforcement Learning for NavigationCode0
From Game-theoretic Multi-agent Log Linear Learning to Reinforcement Learning—0
Efficient collective swimming by harnessing vortices through deep reinforcement learning—0
Deep Reinforcement Learning for Image Hashing—0
Decomposition Methods with Deep Corrections for Reinforcement LearningCode0
Shared Autonomy via Deep Reinforcement LearningCode0
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner ArchitecturesCode1
Coordinated Exploration in Concurrent Reinforcement Learning—0
Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement LearningCode0
Multi-task Learning for Continuous Control—0
Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making—0
Deep Reinforcement Learning for Programming Language CorrectionCode0
Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations—0
Barrier-Certified Adaptive Reinforcement Learning with Applications to Brushbot Navigation—0
Deep Reinforcement Learning using Capsules in Advanced Game Environments—0
Learning the Reward Function for a Misspecified ModelCode0
Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data—0
FlashRL: A Reinforcement Learning Platform for Flash Games—0
Safe Exploration in Continuous Action SpacesCode1
Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods—0
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning AgentsCode0
Logically-Constrained Reinforcement LearningCode1
Analyzing Language Learned by an Active Question Answering Agent—0
Curiosity-driven reinforcement learning with homeostatic regulation—0
Cross-Domain Transfer in Reinforcement Learning using Target Apprentice—0
A Deep Reinforcement Learning Chatbot (Short Version)—0
Learning model-based strategies in simple environments with hierarchical q-networksCode0
Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy LearningCode0
Experience-driven Networking: A Deep Reinforcement Learning based Approach—0
The Case for Automatic Database Administration using Deep Reinforcement Learning—0
Reinforcement Learning based Recommender System using Biclustering Technique—0
The QLBS Q-Learner Goes NuQLear: Fitted Q Iteration, Inverse RL, and Option Portfolios—0
Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management—0
GitGraph - Architecture Search Space Creation through Frequent Computational Subgraph Mining—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified