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

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Showing 1951–2000 of 15113 papers

TitleStatusHype
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-CriticCode1
Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement LearningCode1
Self-critical Sequence Training for Image CaptioningCode1
Self-Driving Network and Service Coordination Using Deep Reinforcement LearningCode1
Self-Paced Deep Reinforcement LearningCode1
Self-Play Reinforcement Learning for Fast Image RetargetingCode1
Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement LearningCode1
Self-supervised Visual Reinforcement Learning with Object-centric RepresentationsCode1
Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement LearningCode1
Sequential Voting with Relational Box Fields for Active Object DetectionCode1
Conditional Mutual Information for Disentangled Representations in Reinforcement LearningCode1
Settling the Variance of Multi-Agent Policy GradientsCode1
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement LearningCode1
SHARPIE: A Modular Framework for Reinforcement Learning and Human-AI Interaction ExperimentsCode1
A Multiplicative Value Function for Safe and Efficient Reinforcement LearningCode1
Shortest-Path Constrained Reinforcement Learning for Sparse Reward TasksCode1
Compositional Reinforcement Learning from Logical SpecificationsCode1
Simple random search provides a competitive approach to reinforcement learningCode1
Basis for Intentions: Efficient Inverse Reinforcement Learning using Past ExperienceCode1
Addressing Function Approximation Error in Actor-Critic MethodsCode1
CompoSuite: A Compositional Reinforcement Learning BenchmarkCode1
Compiler Optimization for Quantum Computing Using Reinforcement LearningCode1
Simulating SQL Injection Vulnerability Exploitation Using Q-Learning Reinforcement Learning AgentsCode1
Batch Exploration with Examples for Scalable Robotic Reinforcement LearningCode1
Competitiveness of MAP-Elites against Proximal Policy Optimization on locomotion tasks in deterministic simulationsCode1
Compile Scene Graphs with Reinforcement LearningCode1
Compound AI Systems Optimization: A Survey of Methods, Challenges, and Future DirectionsCode1
Skill-Based Reinforcement Learning with Intrinsic Reward MatchingCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement LearningCode1
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy MatchingCode1
SMPL: Simulated Industrial Manufacturing and Process Control Learning EnvironmentsCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement LearningCode1
Soft Actor-Critic Deep Reinforcement Learning for Fault Tolerant Flight ControlCode1
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loopCode1
Soft Hindsight Experience ReplayCode1
Bayesian Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement LearningCode1
Solving Compositional Reinforcement Learning Problems via Task ReductionCode1
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level PaintingsCode1
Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement LearningCode1
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMsCode1
CommonPower: A Framework for Safe Data-Driven Smart Grid ControlCode1
Spatial-temporal recurrent reinforcement learning for autonomous shipsCode1
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation PerspectiveCode1
Bayesian Generational Population-Based TrainingCode1
SplAgger: Split Aggregation for Meta-Reinforcement LearningCode1
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman ProblemCode1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
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Benchmark Results

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