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 5751–5775 of 15113 papers

TitleStatusHype
A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images—0
General sum stochastic games with networked information flows—0
A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning—0
Multi-Agent Deep Reinforcement Learning in Vehicular OCC—0
Rapid Locomotion via Reinforcement Learning—0
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning—0
Multivariate Prediction Intervals for Random ForestsCode1
State Representation Learning for Goal-Conditioned Reinforcement Learning—0
Exploring the Benefits of Teams in Multiagent Learning—0
Using Deep Reinforcement Learning to solve Optimal Power Flow problem with generator failures—0
Multi-subgoal Robot Navigation in Crowds with History Information and Interactions—0
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars—0
RLFlow: Optimising Neural Network Subgraph Transformation with World ModelsCode0
Triangular Dropout: Variable Network Width without Retraining—0
Exploration in Deep Reinforcement Learning: A Survey—0
Large Neighborhood Search based on Neural Construction HeuristicsCode1
Deep-Attack over the Deep Reinforcement Learning—0
CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement LearningCode1
Integrating Question Rewrites in Conversational Question Answering: A Reinforcement Learning Approach—0
Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation—0
Reinforced Cross-modal Alignment for Radiology Report GenerationCode0
[CASPI] Causal-aware Safe Policy Improvement for Task-oriented Dialogue—0
Processing Network Controls via Deep Reinforcement Learning—0
Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach—0
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning—0
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Benchmark Results

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