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 45014525 of 15113 papers

TitleStatusHype
VerIPO: Cultivating Long Reasoning in Video-LLMs via Verifier-Gudied Iterative Policy OptimizationCode0
Viability of Future Actions: Robust Safety in Reinforcement Learning via Entropy RegularizationCode0
Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate withCode0
Model-Based Reinforcement Learning with Multi-Task Offline PretrainingCode0
ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement LearningCode0
Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement LearningCode0
Reinforcement Learning for Channel Coding: Learned Bit-Flipping DecodingCode0
Marvel: Accelerating Safe Online Reinforcement Learning with Finetuned Offline PolicyCode0
Viewpoint Optimization for Autonomous Strawberry Harvesting with Deep Reinforcement LearningCode0
VIME: Variational Information Maximizing ExplorationCode0
VINE: An Open Source Interactive Data Visualization Tool for NeuroevolutionCode0
VIREL: A Variational Inference Framework for Reinforcement LearningCode0
Virtual Augmented Reality for Atari Reinforcement LearningCode0
Virtual Replay CacheCode0
Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement LearningCode0
Virtual to Real Reinforcement Learning for Autonomous DrivingCode0
Reinforcement Learning for Control of Non-Markovian Cellular Population DynamicsCode0
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological RewardsCode0
Vision-based Navigation Using Deep Reinforcement LearningCode0
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement LearningCode0
Neural Episodic ControlCode0
Neural Improvement Heuristics for Graph Combinatorial Optimization ProblemsCode0
Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic ControlCode0
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANsCode0
POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenanceCode0
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Benchmark Results

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