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 1576–1600 of 15113 papers

TitleStatusHype
Discriminator-Weighted Offline Imitation Learning from Suboptimal DemonstrationsCode1
DISK: Learning local features with policy gradientCode1
Multi-Agent Task-Oriented Dialog Policy Learning with Role-Aware Reward DecompositionCode1
A Deep Reinforced Model for Abstractive SummarizationCode1
Generalizing Across Multi-Objective Reward Functions in Deep Reinforcement LearningCode1
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot ManipulationCode1
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement LearningCode1
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics NetworkCode1
Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement LearningCode1
Multi-Objective reward generalization: Improving performance of Deep Reinforcement Learning for applications in single-asset tradingCode1
Distributed Control of Partial Differential Equations Using Convolutional Reinforcement LearningCode1
Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal ReasoningCode1
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement LearningCode1
Batch Exploration with Examples for Scalable Robotic Reinforcement LearningCode1
Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V CommunicationCode1
Distributional Reinforcement Learning with Unconstrained Monotonic Neural NetworksCode1
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous ControlCode1
Learning Robust State Abstractions for Hidden-Parameter Block MDPsCode1
Multi-Task Reinforcement Learning with Context-based RepresentationsCode1
Distributional Reinforcement Learning via Moment MatchingCode1
Multi Type Mean Field Reinforcement LearningCode1
A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement LearningCode1
A SWAT-based Reinforcement Learning Framework for Crop ManagementCode1
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience ReplayCode1
Generalized Decision Transformer for Offline Hindsight Information MatchingCode1
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Benchmark Results

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