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 1701–1750 of 15113 papers

TitleStatusHype
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation TasksCode1
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous DrivingCode1
Batch Exploration with Examples for Scalable Robotic Reinforcement LearningCode1
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum GamesCode1
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-EnsembleCode1
Off-Policy Adversarial Inverse Reinforcement LearningCode1
Automatic Data Augmentation for Generalization in Deep Reinforcement LearningCode1
Communicative Reinforcement Learning Agents for Landmark Detection in Brain ImagesCode1
Compile Scene Graphs with Reinforcement LearningCode1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
Procedural generation of meta-reinforcement learning tasksCode1
Provably Efficient Online Hyperparameter Optimization with Population-Based BanditsCode1
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics TasksCode1
On Joint Learning for Solving Placement and Routing in Chip DesignCode1
Combining Modular Skills in Multitask LearningCode1
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement LearningCode1
Online Intrinsic Rewards for Decision Making Agents from Large Language Model FeedbackCode1
Online Portfolio Management via Deep Reinforcement Learning with High-Frequency DataCode1
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction EstimationCode1
On Penalty-based Bilevel Gradient Descent MethodCode1
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agentsCode1
On Reinforcement Learning for the Game of 2048Code1
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman ProblemCode1
On the Importance of Hyperparameter Optimization for Model-based Reinforcement LearningCode1
On the model-based stochastic value gradient for continuous reinforcement learningCode1
On the Robustness of Cooperative Multi-Agent Reinforcement LearningCode1
Combining Deep Reinforcement Learning and Search for Imperfect-Information GamesCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Learning to combine primitive skills: A step towards versatile robotic manipulationCode1
Combining Reinforcement Learning with Model Predictive Control for On-Ramp MergingCode1
Agent Modelling under Partial Observability for Deep Reinforcement LearningCode1
Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image TranslationCode1
Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning AlgorithmCode1
Optimal Goal-Reaching Reinforcement Learning via Quasimetric LearningCode1
A Learning System for Motion Planning of Free-Float Dual-Arm Space Manipulator towards Non-Cooperative ObjectCode1
Bayesian Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
Optimistic Exploration even with a Pessimistic InitialisationCode1
Single-step deep reinforcement learning for open-loop control of laminar and turbulent flowsCode1
Optimization of the Model Predictive Control Update Interval Using Reinforcement LearningCode1
Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley ValuesCode1
Optimizing Large-Scale Fleet Management on a Road Network using Multi-Agent Deep Reinforcement Learning with Graph Neural NetworkCode1
Optimizing Quantum Variational Circuits with Deep Reinforcement LearningCode1
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement LearningCode1
Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic ApproachCode1
ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization ProblemsCode1
OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical LocomotionCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
PaCo: Parameter-Compositional Multi-Task Reinforcement LearningCode1
PantheonRL: A MARL Library for Dynamic Training InteractionsCode1
Collision Probability Distribution Estimation via Temporal Difference LearningCode1
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Benchmark Results

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