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 9951–10000 of 15113 papers

TitleStatusHype
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs—0
Flightmare: A Flexible Quadrotor SimulatorCode2
Data-driven Outer-Loop Control Using Deep Reinforcement Learning for Trajectory Tracking—0
Beyond variance reduction: Understanding the true impact of baselines on policy optimization—0
Control of a Nature-inspired Scorpion using Reinforcement Learning—0
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL—0
Ranking Policy DecisionsCode0
Deep Reinforcement Learning for Contact-Rich Skills Using Compliant Movement Primitives—0
Human-in-the-Loop Methods for Data-Driven and Reinforcement Learning Systems—0
How does the structure embedded in learning policy affect learning quadruped locomotion?—0
Reinforcement Learning with Feedback-modulated TD-STDP—0
Real-world Video Adaptation with Reinforcement Learning—0
Sample Efficiency in Sparse Reinforcement Learning: Or Your Money Back—0
Meta Reinforcement Learning-Based Lane Change Strategy for Autonomous Vehicles—0
On the model-based stochastic value gradient for continuous reinforcement learningCode1
Query Focused Multi-document Summarisation of Biomedical Texts: Macquarie Universiy and the Australian National University at BioASQ8bCode0
Market-making with reinforcement-learning (SAC)Code1
Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning—0
AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement LearningCode0
Document-editing Assistants and Model-based Reinforcement Learning as a Path to Conversational AI—0
The Advantage Regret-Matching Actor-Critic—0
Query Focused Multi-document Summarisation of Biomedical TextsCode0
Selective Particle Attention: Visual Feature-Based Attention in Deep Reinforcement Learning—0
Synthetic Sample Selection via Reinforcement Learning—0
Identifying Critical States by the Action-Based Variance of Expected Return—0
Constrained Markov Decision Processes via Backward Value Functions—0
Decision-making for Autonomous Vehicles on Highway: Deep Reinforcement Learning with Continuous Action Horizon—0
Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation—0
t-Soft Update of Target Network for Deep Reinforcement Learning—0
Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing—0
Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning—0
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep Reinforcement Learning Approach—0
Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning—0
Improved Memories Learning—0
Learning Off-Policy with Online PlanningCode1
DSP: A Differential Spatial Prediction Scheme for Comprehensive real industrial datasets—0
Adaptive and Multiple Time-scale Eligibility Traces for Online Deep Reinforcement Learning—0
Mobile Networks for Computer Go—0
Social-Aware Incentive Mechanism for VehicularCrowdsensing by Deep Reinforcement LearningCode1
Model-Free Episodic Control with State Aggregation—0
Biomechanic Posture Stabilisation via Iterative Training of Multi-policy Deep Reinforcement Learning Agents—0
Adversarial Imitation Learning via Random Search—0
Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication—0
A Composable Specification Language for Reinforcement Learning TasksCode1
Reinforcement Learning-based Admission Control in Delay-sensitive Service Systems—0
NANCY: Neural Adaptive Network Coding methodologY for video distribution over wireless networks—0
Static Neural Compiler Optimization via Deep Reinforcement Learning—0
Model-free optimal control of discrete-time systems with additive and multiplicative noises—0
Reinforcement Learning based dynamic weighing of Ensemble Models for Time Series Forecasting—0
Optimal control towards sustainable wastewater treatment plants based on multi-agent reinforcement learningCode1
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Benchmark Results

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