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 726–750 of 15113 papers

TitleStatusHype
Discrete Codebook World Models for Continuous ControlCode1
Accelerating Reinforcement Learning with Learned Skill PriorsCode1
Barrier Certified Safety Learning Control: When Sum-of-Square Programming Meets Reinforcement LearningCode1
Basis for Intentions: Efficient Inverse Reinforcement Learning using Past ExperienceCode1
Batch Exploration with Examples for Scalable Robotic Reinforcement LearningCode1
Actor-Critic Reinforcement Learning for Control with Stability GuaranteeCode1
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningCode1
A Game-Theoretic Approach to Multi-Agent Trust Region OptimizationCode1
Bayesian Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
BEAR: Physics-Principled Building Environment for Control and Reinforcement LearningCode1
Behavior From the Void: Unsupervised Active Pre-TrainingCode1
BCORLE(): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce MarketCode1
BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGymCode1
A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement LearningCode1
Distributed Online Service Coordination Using Deep Reinforcement LearningCode1
A General Contextualized Rewriting Framework for Text SummarizationCode1
Deep Reinforcement Learning from Self-Play in Imperfect-Information GamesCode1
Adversarially Trained Actor Critic for Offline Reinforcement LearningCode1
Behavior Proximal Policy OptimizationCode1
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlowCode1
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement LearningCode1
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning StudyCode1
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action ConstraintsCode1
DMC-VB: A Benchmark for Representation Learning for Control with Visual DistractorsCode1
A SWAT-based Reinforcement Learning Framework for Crop ManagementCode1
Show:102550
← PrevPage 30 of 605Next →

Benchmark Results

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