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 351–400 of 15113 papers

TitleStatusHype
A Cooperation Graph Approach for Multiagent Sparse Reward Reinforcement LearningCode2
Dialogue Learning With Human-In-The-LoopCode2
Diffusion Actor-Critic with Entropy RegulatorCode2
EfficientZero V2: Mastering Discrete and Continuous Control with Limited DataCode2
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement LearningCode2
AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with TransformersCode2
Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical RobotCode2
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement LearningCode2
AMP: Adversarial Motion Priors for Stylized Physics-Based Character ControlCode2
Challenges and Opportunities in Offline Reinforcement Learning from Visual ObservationsCode2
MO-Gym: A Library of Multi-Objective Reinforcement Learning EnvironmentsCode2
MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement LearningCode2
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics ModelsCode2
A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement LearningCode2
Multi-Agent Reinforcement Learning is a Sequence Modeling ProblemCode2
GenRL: Multimodal-foundation world models for generalization in embodied agentsCode2
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph MatchingCode2
Deep Reinforcement Learning for Multi-Agent InteractionCode2
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal SystemsCode2
NoisyRollout: Reinforcing Visual Reasoning with Data AugmentationCode2
ODRL: A Benchmark for Off-Dynamics Reinforcement LearningCode2
Offline Reinforcement Learning for LLM Multi-Step ReasoningCode2
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, ChallengesCode2
Datasets and Benchmarks for Offline Safe Reinforcement LearningCode2
D4RL: Datasets for Deep Data-Driven Reinforcement LearningCode2
Curiosity-driven Red-teaming for Large Language ModelsCode2
Assessment of Reinforcement Learning for Macro PlacementCode2
DayDreamer: World Models for Physical Robot LearningCode2
Think or Not Think: A Study of Explicit Thinking in Rule-Based Visual Reinforcement Fine-TuningCode2
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningCode2
AndroidEnv: A Reinforcement Learning Platform for AndroidCode2
Craftium: An Extensible Framework for Creating Reinforcement Learning EnvironmentsCode2
AutoTriton: Automatic Triton Programming with Reinforcement Learning in LLMsCode2
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem SolvingCode2
CTR-Driven Advertising Image Generation with Multimodal Large Language ModelsCode2
Decoupling Representation Learning from Reinforcement LearningCode2
Developing A Multi-Agent and Self-Adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk ManagementCode2
ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement LearningCode2
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning BenchmarksCode2
Physics-based Deep LearningCode2
A simple but strong baseline for online continual learning: Repeated Augmented RehearsalCode1
A Comprehensive Survey of Data Augmentation in Visual Reinforcement LearningCode1
Control-Informed Reinforcement Learning for Chemical ProcessesCode1
A Composable Specification Language for Reinforcement Learning TasksCode1
A Boolean Task Algebra for Reinforcement LearningCode1
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning AlgorithmsCode1
Controlling the Risk of Conversational Search via Reinforcement LearningCode1
Contrastive State Augmentations for Reinforcement Learning-Based Recommender SystemsCode1
Scalable Multi-agent Reinforcement Learning Algorithm for Wireless NetworksCode1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement LearningCode1
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Benchmark Results

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