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 4251–4275 of 15113 papers

TitleStatusHype
Addressing Moral Uncertainty using Large Language Models for Ethical Decision-Making—0
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning—0
Addressing the issue of stochastic environments and local decision-making in multi-objective reinforcement learning—0
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment—0
A Decentralized Communication Framework based on Dual-Level Recurrence for Multi-Agent Reinforcement Learning—0
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning—0
A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles—0
A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access—0
A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control—0
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning—0
A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming—0
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games—0
A deep learning model for gas storage optimization—0
A Deep Neural Network Algorithm for Linear-Quadratic Portfolio Optimization with MGARCH and Small Transaction Costs—0
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise—0
A Deep Reinforcement Learning Approach towards Pendulum Swing-up Problem based on TF-Agents—0
A Deep-Reinforcement Learning Approach for Software-Defined Networking Routing Optimization—0
A Deep Reinforcement Learning Approach for Composing Moving IoT Services—0
A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback—0
A Deep Reinforcement Learning Approach for Ramp Metering Based on Traffic Video Data—0
A Deep Reinforcement Learning Approach for the Meal Delivery Problem—0
A Deep Reinforcement Learning Approach for Traffic Signal Control Optimization—0
A Deep Reinforcement Learning Approach for Fair Traffic Signal Control—0
A Deep Reinforcement Learning Approach for Online Parcel Assignment—0
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments—0
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Benchmark Results

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