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 11701–11750 of 15113 papers

TitleStatusHype
Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor ControlCode0
Momentum in Reinforcement Learning—0
Good, Better, Best: Textual Distractors Generation for Multiple-Choice Visual Question Answering via Reinforcement Learning—0
Adversarial Skill Networks: Unsupervised Robot Skill Learning from VideoCode0
Deep Reinforcement Learning Control of Quantum CartpolesCode1
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning—0
Dealing with Sparse Rewards in Reinforcement LearningCode0
Autonomous Industrial Management via Reinforcement Learning: Self-Learning Agents for Decision-Making -- A Review—0
RLScheduler: An Automated HPC Batch Job Scheduler Using Reinforcement LearningCode0
Policy Learning for Malaria ControlCode0
Towards More Sample Efficiency in Reinforcement Learning with Data AugmentationCode0
Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence ModelCode0
Opinion shaping in social networks using reinforcement learning—0
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement LearningCode0
Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning—0
Explainable AI: Deep Reinforcement Learning Agents for Residential Demand Side Cost Savings in Smart Grids—0
OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research—0
Multi-View Reinforcement LearningCode0
On Connections between Constrained Optimization and Reinforcement Learning—0
On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation—0
Unsupervised Context Rewriting for Open Domain Conversation—0
Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics—0
Adaptive Discretization for Episodic Reinforcement Learning in Metric SpacesCode0
Adaptive Curriculum Generation from Demonstrations for Sim-to-Real Visuomotor ControlCode0
Single Episode Policy Transfer in Reinforcement LearningCode0
Reinforcement Learning for Robotic Manipulation using Simulated Locomotion DemonstrationsCode0
Soft Actor-Critic for Discrete Action SettingsCode0
Parallel Exploration via Negatively Correlated Search—0
Reinforced Bit Allocation under Task-Driven Semantic Distortion Metrics—0
On Learning Paradigms for the Travelling Salesman ProblemCode1
Adaptive Trade-Offs in Off-Policy Learning—0
Creativity in Robot Manipulation with Deep Reinforcement Learning—0
Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use caseCode0
Conditional Importance Sampling for Off-Policy Learning—0
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision ProcessesCode0
Reinforcement learning with a network of spiking agentsCode1
Dynamic Graph Configuration with Reinforcement Learning for Connected Autonomous Vehicle Trajectories—0
A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme—0
Actor Critic with Differentially Private Critic—0
On the Expressivity of Neural Networks for Deep Reinforcement LearningCode0
Coordination of PV Smart Inverters Using Deep Reinforcement Learning for Grid Voltage Regulation—0
Federated Transfer Reinforcement Learning for Autonomous Driving—0
On the Reduction of Variance and Overestimation of Deep Q-Learning—0
Rethinking Exposure Bias In Language Modeling—0
Stabilizing Transformers for Reinforcement LearningCode1
Policy Poisoning in Batch Reinforcement Learning and ControlCode0
QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning—0
Neural Program Synthesis By Self-Learning—0
Curiosity-Driven Recommendation Strategy for Adaptive Learning via Deep Reinforcement Learning—0
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer LearningCode0
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Benchmark Results

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