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

Showing 33513400 of 15113 papers

TitleStatusHype
Policy Synthesis and Reinforcement Learning for Discounted LTL0
A Reminder of its Brittleness: Language Reward Shaping May Hinder Learning for Instruction Following AgentsCode0
Distributional Reinforcement Learning with Dual Expectile-Quantile Regression0
Learning Interpretable Models of Aircraft Handling Behaviour by Reinforcement Learning from Human Feedback0
Generating Synergistic Formulaic Alpha Collections via Reinforcement LearningCode3
Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and MemoryCode2
Reward-Machine-Guided, Self-Paced Reinforcement LearningCode0
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion ModelsCode0
End-to-End Meta-Bayesian Optimisation with Transformer Neural ProcessesCode0
Deterministic policy gradient based optimal control with probabilistic constraints0
Market Making with Deep Reinforcement Learning from Limit Order BooksCode1
PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement LearningCode1
Decision-Aware Actor-Critic with Function Approximation and Theoretical GuaranteesCode0
Control invariant set enhanced safe reinforcement learning: improved sampling efficiency, guaranteed stability and robustness0
Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure0
Deep Reinforcement Learning with Plasticity Injection0
SPRING: Studying the Paper and Reasoning to Play GamesCode1
A Mini Review on the utilization of Reinforcement Learning with OPC UA0
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement LearningCode1
Conditional Mutual Information for Disentangled Representations in Reinforcement LearningCode1
When should we prefer Decision Transformers for Offline Reinforcement Learning?Code1
Constrained Proximal Policy Optimization0
ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry0
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning0
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML0
Lagrangian-based online safe reinforcement learning for state-constrained systems0
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and PracticeCode0
Policy Representation via Diffusion Probability Model for Reinforcement LearningCode1
INVICTUS: Optimizing Boolean Logic Circuit Synthesis via Synergistic Learning and Search0
Offline Primal-Dual Reinforcement Learning for Linear MDPs0
Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations0
FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex ManipulationCode2
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning0
BertRLFuzzer: A BERT and Reinforcement Learning Based FuzzerCode0
SneakyPrompt: Jailbreaking Text-to-image Generative ModelsCode1
Model-based adaptation for sample efficient transfer in reinforcement learning control of parameter-varying systems0
Understanding the World to Solve Social Dilemmas Using Multi-Agent Reinforcement Learning0
Learning Diverse Risk Preferences in Population-based Self-playCode1
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond0
Contrastive State Augmentations for Reinforcement Learning-Based Recommender SystemsCode1
Client Selection for Federated Policy Optimization with Environment HeterogeneityCode0
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL0
Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional CurriculumCode1
A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning PoliciesCode0
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning0
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCSCode0
Revisiting the Minimalist Approach to Offline Reinforcement LearningCode1
Cooperation Is All You Need0
Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions0
Coagent Networks: Generalized and Scaled0
Show:102550
← PrevPage 68 of 303Next →

Benchmark Results

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