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 951–975 of 15113 papers

TitleStatusHype
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement LearningCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Semi-Supervised Offline Reinforcement Learning with Action-Free TrajectoriesCode1
Reliable Conditioning of Behavioral Cloning for Offline Reinforcement LearningCode1
Multi-Object Navigation with dynamically learned neural implicit representationsCode1
DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement LearningCode1
Exploration via Elliptical Episodic BonusesCode1
A Comprehensive Survey of Data Augmentation in Visual Reinforcement LearningCode1
Benchmarking Reinforcement Learning Techniques for Autonomous NavigationCode1
Multiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation ControlCode1
Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement LearningCode1
Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweeningCode1
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement LearningCode1
BAFFLE: Hiding Backdoors in Offline Reinforcement Learning DatasetsCode1
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationCode1
Exploration via Planning for Information about the Optimal TrajectoryCode1
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill DiscoveryCode1
Rainier: Reinforced Knowledge Introspector for Commonsense Question AnsweringCode1
Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet DetectionCode1
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic ControlCode1
DreamShard: Generalizable Embedding Table Placement for Recommender SystemsCode1
Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote ComputersCode1
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learningCode1
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy OptimizationCode1
Latent State Marginalization as a Low-cost Approach for Improving ExplorationCode1
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Benchmark Results

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