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 7701–7750 of 15113 papers

TitleStatusHype
Tianshou: a Highly Modularized Deep Reinforcement Learning LibraryCode3
Non-Markovian Reinforcement Learning using Fractional Dynamics—0
Lyapunov-based uncertainty-aware safe reinforcement learning—0
Packet Routing with Graph Attention Multi-agent Reinforcement Learning—0
Value-Based Reinforcement Learning for Continuous Control Robotic Manipulation in Multi-Task Sparse Reward Settings—0
Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation—0
A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming—0
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward AlgorithmCode1
Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment—0
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning—0
Reinforcement Learning with Formal Performance Metrics for Quadcopter Attitude Control under Non-nominal Contexts—0
Autonomous Reinforcement Learning via Subgoal Curricula—0
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent—0
Playtesting: What is Beyond Personas—0
Reinforced Imitation Learning by Free Energy Principle—0
DR2L: Surfacing Corner Cases to Robustify Autonomous Driving via Domain Randomization Reinforcement Learning—0
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning—0
Learning Quadruped Locomotion Policies using Logical Rules—0
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare SettingsCode1
A reinforcement learning approach to resource allocation in genomic selection—0
Accelerating Quadratic Optimization with Reinforcement LearningCode1
A Deep Reinforcement Learning Approach for Fair Traffic Signal Control—0
Demonstration-Guided Reinforcement Learning with Learned SkillsCode1
Bayesian Controller Fusion: Leveraging Control Priors in Deep Reinforcement Learning for Robotics—0
MarsExplorer: Exploration of Unknown Terrains via Deep Reinforcement Learning and Procedurally Generated EnvironmentsCode1
Reinforcement Learning Agent Training with Goals for Real World Tasks—0
Proximal Policy Optimization for Tracking Control Exploiting Future Reference Information—0
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement LearningCode1
Improved Reinforcement Learning in Cooperative Multi-agent Environments Using Knowledge Transfer—0
Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural LanguageCode0
Learning Altruistic Behaviours in Reinforcement Learning without External Rewards—0
A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement LearningCode1
Reward-Weighted Regression Converges to a Global OptimumCode0
Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning—0
Provably Efficient Multi-Task Reinforcement Learning with Model Transfer—0
Structured World Belief for Reinforcement Learning in POMDP—0
An Analysis of Reinforcement Learning for Malaria Control—0
Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration—0
Constraints Penalized Q-learning for Safe Offline Reinforcement Learning—0
A New Representation of Successor Features for Transfer across Dissimilar Environments—0
Co-designing Intelligent Control of Building HVACs and MicrogridsCode1
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement LearningCode1
Megaverse: Simulating Embodied Agents at One Million Experiences per SecondCode1
On the Robustness of Deep Reinforcement Learning in IRS-Aided Wireless Communications Systems—0
High-Accuracy Model-Based Reinforcement Learning, a Survey—0
Hierarchical Reinforcement Learning with Optimal Level Synchronization based on a Deep Generative ModelCode0
Learning Heuristics for Template-based CEGIS of Loop Invariants with Reinforcement Learning—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning—0
Decentralized Multi-Agent Reinforcement Learning for Task Offloading Under Uncertainty—0
Show:102550
← PrevPage 155 of 303Next →

Benchmark Results

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