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 10551–10575 of 15113 papers

TitleStatusHype
Model-Based Reinforcement Learning with Value-Targeted Regression—0
Robust Reinforcement Learning with Wasserstein Constraint—0
Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology—0
Temporal-Differential Learning in Continuous Environments—0
PlanGAN: Model-based Planning With Sparse Rewards and Multiple GoalsCode1
A novel approach for multi-agent cooperative pursuit to capture grouped evaders—0
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement LearningCode1
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulasCode1
Acme: A Research Framework for Distributed Reinforcement LearningCode1
Variational Reward Estimator Bottleneck: Learning Robust Reward Estimator for Multi-Domain Task-Oriented Dialog—0
MM-KTD: Multiple Model Kalman Temporal Differences for Reinforcement LearningCode0
Reinforcement LearningCode0
Sim2Real for Peg-Hole Insertion with Eye-in-Hand CameraCode1
AI-based Resource Allocation: Reinforcement Learning for Adaptive Auto-scaling in Serverless Environments—0
Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environmentsCode1
Intelligent Residential Energy Management System using Deep Reinforcement Learning—0
Domain Knowledge Integration By Gradient Matching For Sample-Efficient Reinforcement Learning—0
Predicting Goal-directed Human Attention Using Inverse Reinforcement LearningCode1
Revisiting Parameter Sharing in Multi-Agent Deep Reinforcement LearningCode0
MOPO: Model-based Offline Policy OptimizationCode1
Anomaly Detection Under Controlled Sensing Using Actor-Critic Reinforcement Learning—0
ALBA : Reinforcement Learning for Video Object SegmentationCode0
Towards intervention-centric causal reasoning in learning agents—0
Modeling Penetration Testing with Reinforcement Learning Using Capture-the-Flag Challenges: Trade-offs between Model-free Learning and A Priori KnowledgeCode1
Time-Variant Variational Transfer for Value Functions—0
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Benchmark Results

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