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 401450 of 15113 papers

TitleStatusHype
When should we prefer Decision Transformers for Offline Reinforcement Learning?Code1
Curriculum Offline Imitation LearningCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
Dataset Reset Policy Optimization for RLHFCode1
CURL: Contrastive Unsupervised Representation Learning for Reinforcement LearningCode1
ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial MarketsCode1
CURL: Contrastive Unsupervised Representations for Reinforcement LearningCode1
Curiosity-Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning ApproachCode1
Curious Hierarchical Actor-Critic Reinforcement LearningCode1
CurricuLLM: Automatic Task Curricula Design for Learning Complex Robot Skills using Large Language ModelsCode1
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Cryptocurrency Portfolio Management with Deep Reinforcement LearningCode1
Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation ErrorsCode1
A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric VehiclesCode1
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement LearningCode1
Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RLCode1
Curriculum-based Asymmetric Multi-task Reinforcement LearningCode1
Cross-Modal Contrastive Learning of Representations for Navigation using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental ConditionsCode1
Cross-Modal Domain Adaptation for Reinforcement LearningCode1
Cross-Domain Policy Adaptation by Capturing Representation MismatchCode1
CropGym: a Reinforcement Learning Environment for Crop ManagementCode1
Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space AlignmentCode1
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement LearningCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
A Benchmark Environment Motivated by Industrial Control ProblemsCode1
Critic Regularized RegressionCode1
A Benchmark Environment for Offline Reinforcement Learning in Racing GamesCode1
Critic-Guided Decision Transformer for Offline Reinforcement LearningCode1
CROP: Conservative Reward for Model-based Offline Policy OptimizationCode1
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
Correlation-aware Cooperative Multigroup Broadcast 360° Video Delivery Network: A Hierarchical Deep Reinforcement Learning ApproachCode1
Counterfactual Data Augmentation using Locally Factored DynamicsCode1
Co-Reinforcement Learning for Unified Multimodal Understanding and GenerationCode1
A coevolutionary approach to deep multi-agent reinforcement learningCode1
CoRL: Environment Creation and Management Focused on System IntegrationCode1
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement LearningCode1
ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging ResearchCode1
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model CheckingCode1
Converting Biomechanical Models from OpenSim to MuJoCoCode1
Addressing Function Approximation Error in Actor-Critic MethodsCode1
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data FormatCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning AgentsCode1
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and SimplicityCode1
Contrastive State Augmentations for Reinforcement Learning-Based Recommender SystemsCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement LearningCode1
Acme: A Research Framework for Distributed Reinforcement LearningCode1
Contrastive Preference Learning: Learning from Human Feedback without RLCode1
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Benchmark Results

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