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 4551–4575 of 15113 papers

TitleStatusHype
A Mini Review on the utilization of Reinforcement Learning with OPC UA—0
A Mixture-of-Expert Approach to RL-based Dialogue Management—0
AMM: Adaptive Modularized Reinforcement Model for Multi-city Traffic Signal Control—0
AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control—0
A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning—0
A model-based approach to meta-Reinforcement Learning: Transformers and tree search—0
A Model-based Multi-Agent Personalized Short-Video Recommender System—0
A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task—0
A Model-Based Reinforcement Learning Approach for PID Design—0
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret—0
A model of discrete choice based on reinforcement learning under short-term memory—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes—0
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem—0
MSPM: A Modularized and Scalable Multi-Agent Reinforcement Learning-based System for Financial Portfolio Management—0
A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications—0
AMRL: Aggregated Memory For Reinforcement Learning—0
A Multiagent CyberBattleSim for RL Cyber Operation Agents—0
A Multi-Agent Deep Reinforcement Learning Approach for a Distributed Energy Marketplace in Smart Grids—0
A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways—0
A Multiagent Reinforcement Learning Algorithm with Non-linear Dynamics—0
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning—0
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising—0
A Multi-Agent Reinforcement Learning Testbed for Cognitive Radio Applications—0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization—0
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Benchmark Results

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