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 3076–3100 of 15113 papers

TitleStatusHype
Neural Categorical Priors for Physics-Based Character Control—0
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models—0
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation—0
A Comparison of Classical and Deep Reinforcement Learning Methods for HVAC Control—0
Provably Efficient Algorithm for Nonstationary Low-Rank MDPs—0
Collaborative Wideband Spectrum Sensing and Scheduling for Networked UAVs in UTM Systems—0
Actor-Critic with variable time discretization via sustained actions—0
Characterization of Human Balance through a Reinforcement Learning-based Muscle Controller—0
Exploiting Generalization in Offline Reinforcement Learning via Unseen State Augmentations—0
A Reinforcement Learning-Based Approach to Graph Discovery in D2D-Enabled Federated Learning—0
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration—0
Reinforcement Learning for Financial Index TrackingCode1
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence GenerationCode1
Nonprehensile Planar Manipulation through Reinforcement Learning with Multimodal Categorical Exploration—0
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback—0
Bag of Policies for Distributional Deep Exploration—0
Revisiting a Design Choice in Gradient Temporal Difference Learning—0
Follow the Soldiers with Optimized Single-Shot Multibox Detection and Reinforcement Learning—0
qgym: A Gym for Training and Benchmarking RL-Based Quantum CompilationCode1
Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman ProblemsCode1
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel OptimizationCode0
Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges—0
End-to-End Reinforcement Learning for Torque Based Variable Height HoppingCode0
DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route PredictionCode1
PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social DilemmasCode0
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Benchmark Results

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