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 45514600 of 15113 papers

TitleStatusHype
A Mini Review on the utilization of Reinforcement Learning with OPC UA0
A Mixture-of-Expert Approach to RL-based Dialogue Management0
AMM: Adaptive Modularized Reinforcement Model for Multi-city Traffic Signal Control0
AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control0
A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning0
A model-based approach to meta-Reinforcement Learning: Transformers and tree search0
A Model-based Multi-Agent Personalized Short-Video Recommender System0
A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task0
A Model-Based Reinforcement Learning Approach for PID Design0
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret0
A model of discrete choice based on reinforcement learning under short-term memory0
A Model Selection Approach for Corruption Robust Reinforcement Learning0
A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes0
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem0
MSPM: A Modularized and Scalable Multi-Agent Reinforcement Learning-based System for Financial Portfolio Management0
A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications0
AMRL: Aggregated Memory For Reinforcement Learning0
A Multiagent CyberBattleSim for RL Cyber Operation Agents0
A Multi-Agent Deep Reinforcement Learning Approach for a Distributed Energy Marketplace in Smart Grids0
A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways0
A Multiagent Reinforcement Learning Algorithm with Non-linear Dynamics0
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning0
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising0
A Multi-Agent Reinforcement Learning Testbed for Cognitive Radio Applications0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization0
A Multifidelity Sim-to-Real Pipeline for Verifiable and Compositional Reinforcement Learning0
A Multimodal Learning-based Approach for Autonomous Landing of UAV0
A MultiModal Social Robot Toward Personalized Emotion Interaction0
A Multi-Objective Deep Reinforcement Learning Framework0
An Abstraction-based Method to Check Multi-Agent Deep Reinforcement-Learning Behaviors0
An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments0
An Actor-Critic Method for Simulation-Based Optimization0
An A* Curriculum Approach to Reinforcement Learning for RGBD Indoor Robot Navigation0
An Adaptable Approach to Learn Realistic Legged Locomotion without Examples0
An Adaptive Multi-Agent Physical Layer Security Framework for Cognitive Cyber-Physical Systems0
An adaptive synchronization approach for weights of deep reinforcement learning0
An advantage based policy transfer algorithm for reinforcement learning with measures of transferability0
An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario0
An agent-driven semantical identifier using radial basis neural networks and reinforcement learning0
I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons0
An Algorithmic Theory of Metacognition in Minds and Machines0
Analog Circuit Design with Dyna-Style Reinforcement Learning0
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient0
Analysing Congestion Problems in Multi-agent Reinforcement Learning0
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation0
Analysis and Improvement of Policy Gradient Estimation0
Analysis of Agent Expertise in Ms. Pac-Man using Value-of-Information-based Policies0
Analysis of Evolutionary Behavior in Self-Learning Media Search Engines0
Analysis of Information Propagation in Ethereum Network Using Combined Graph Attention Network and Reinforcement Learning to Optimize Network Efficiency and Scalability0
Analysis of Randomization Effects on Sim2Real Transfer in Reinforcement Learning for Robotic Manipulation Tasks0
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Benchmark Results

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