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 12851–12900 of 15113 papers

TitleStatusHype
Introspection Learning—0
Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks—0
Diagnosing Bottlenecks in Deep Q-learning AlgorithmsCode0
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies—0
Learning When Not to Answer: A Ternary Reward Structure for Reinforcement Learning based Question Answering—0
Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings—0
Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?—0
Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and AnimalsCode0
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence—0
Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots—0
S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay—0
Long-Range Indoor Navigation with PRM-RL—0
Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning—0
Distributionally Robust Reinforcement Learning—0
A General Framework for Structured Learning of Mechanical SystemsCode0
Generative Memory for Lifelong Reinforcement Learning—0
Learning Deterministic Policy with Target for Power Control in Wireless Networks—0
Statistics and Samples in Distributional Reinforcement Learning—0
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following—0
Curiosity-Driven Experience Prioritization via Density Estimation—0
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPsCode0
Deep Reinforcement Learning using Genetic Algorithm for Parameter OptimizationCode0
DOM-Q-NET: Grounded RL on Structured LanguageCode0
A novel repetition normalized adversarial reward for headline generation—0
Emergent Coordination Through Competition—0
Hyperbolic Discounting and Learning over Multiple HorizonsCode0
Investigating Generalisation in Continuous Deep Reinforcement Learning—0
Parenting: Safe Reinforcement Learning from Human Input—0
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning—0
A new Potential-Based Reward Shaping for Reinforcement Learning Agent—0
Heuristics, Answer Set Programming and Markov Decision Process for Solving a Set of Spatial PuzzlesCode0
Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning—0
Asynchronous Coagent Networks—0
Deep Reinforcement Learning Based High-level Driving Behavior Decision-making Model in Heterogeneous Traffic—0
Robust Reinforcement Learning in POMDPs with Incomplete and Noisy Observations—0
Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement LearningCode0
Unsupervised Visuomotor Control through Distributional Planning NetworksCode0
Verifiably Safe Off-Model Reinforcement LearningCode1
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and SimplicityCode1
Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning—0
Reinforcement Learning for UA V Attitude Control—0
Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems—0
Preferences Implicit in the State of the WorldCode0
ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning—0
Deep Reinforcement Learning from Policy-Dependent Human Feedback—0
Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous FlightCode0
Latent Space Reinforcement Learning for Steering Angle Prediction—0
Performance Dynamics and Termination Errors in Reinforcement Learning: A Unifying Perspective—0
WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving—0
Stochastic Reinforcement Learning—0
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Benchmark Results

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