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

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Showing 3051–3100 of 15113 papers

TitleStatusHype
Language Reward Modulation for Pretraining Reinforcement LearningCode1
RamseyRL: A Framework for Intelligent Ramsey Number Counterexample SearchingCode0
Towards Validating Long-Term User Feedbacks in Interactive Recommendation Systems—0
LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient QueryingCode0
A Homogenization Approach for Gradient-Dominated Stochastic Optimization—0
Stabilizing Unsupervised Environment Design with a Learned Adversary—0
Soft Decomposed Policy-Critic: Bridging the Gap for Effective Continuous Control with Discrete RL—0
Accelerating Exact Combinatorial Optimization via RL-based Initialization -- A Case Study in Scheduling—0
UAV-assisted Semantic Communication with Hybrid Action Reinforcement Learning—0
Reinforced Self-Training (ReST) for Language Modeling—0
Data-driven Integrated Sensing and Communication: Recent Advances, Challenges, and Future Prospects—0
ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents—0
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games—0
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making—0
Partially Observable Multi-Agent Reinforcement Learning with Information Sharing—0
Planning to Learn: A Novel Algorithm for Active Learning during Model-Based PlanningCode0
A Reinforcement Learning Approach for Performance-aware Reduction in Power Consumption of Data Center Compute NodesCode0
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World—0
On-demand Cold Start Frequency Reduction with Off-Policy Reinforcement Learning in Serverless Computing—0
ACRE: Actor-Critic with Reward-Preserving ExplorationCode0
IOB: Integrating Optimization Transfer and Behavior Transfer for Multi-Policy Reuse—0
Dialogue for Prompting: a Policy-Gradient-Based Discrete Prompt Generation for Few-shot LearningCode1
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads—0
Omega-Regular Reward Machines—0
Insurance pricing on price comparison websites via reinforcement learning—0
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