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 6451–6475 of 15113 papers

TitleStatusHype
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning—0
Cooperative Actor-Critic via TD Error Aggregation—0
Flowsheet synthesis through hierarchical reinforcement learning and graph neural networks—0
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration—0
Online Reinforcement Learning for Periodic MDP—0
Adaptive Asynchronous Control Using Meta-learned Neural Ordinary Differential Equations—0
Post-processing Networks: Method for Optimizing Pipeline Task-oriented Dialogue Systems using Reinforcement LearningCode0
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery—0
Anti-Overestimation Dialogue Policy Learning for Task-Completion Dialogue System—0
Halftoning with Multi-Agent Deep Reinforcement Learning—0
Epersist: A Self Balancing Robot Using PID Controller And Deep Reinforcement Learning—0
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution—0
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement LearningCode0
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning—0
Detecting Small Query Graphs in A Large Graph via Neural Subgraph Search—0
Strategising template-guided needle placement for MR-targeted prostate biopsy—0
Multi-Asset Closed-Loop Reservoir Management Using Deep Reinforcement Learning—0
Solving the optimal stopping problem with reinforcement learning: an application in financial option exerciseCode0
Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning—0
On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RANCode0
Successor Representation Active InferenceCode0
Quantifying the Effect of Feedback Frequency in Interactive Reinforcement Learning for Robotic Tasks—0
Riemannian Stochastic Gradient Method for Nested Composition Optimization—0
Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement LearningCode0
New Auction Algorithms for Path Planning, Network Transport, and Reinforcement Learning—0
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Benchmark Results

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