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 551–600 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning at the Edge of the Statistical PrecipiceCode1
Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest OverfittingCode1
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum GamesCode1
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent SpaceCode1
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous DrivingCode1
A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewardsCode1
Deep Laplacian-based Options for Temporally-Extended ExplorationCode1
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character SkillsCode1
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight DeliveryCode1
Augmenting Policy Learning with Routines Discovered from a Single DemonstrationCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation TasksCode1
Deep Deterministic Portfolio OptimizationCode1
Deep Intrinsically Motivated Exploration in Continuous ControlCode1
DeepMind Control SuiteCode1
Deep Reinforcement Learning for Active High Frequency TradingCode1
Attention Actor-Critic algorithm for Multi-Agent Constrained Co-operative Reinforcement LearningCode1
Decoupling Strategy and Generation in Negotiation DialoguesCode1
Decoupling Value and Policy for Generalization in Reinforcement LearningCode1
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority InfluenceCode1
Attacking Video Recognition Models with Bullet-Screen CommentsCode1
Deep Active Inference for Partially Observable MDPsCode1
A Traffic Light Dynamic Control Algorithm with Deep Reinforcement Learning Based on GNN PredictionCode1
Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement LearningCode1
A Text-based Deep Reinforcement Learning Framework for Interactive RecommendationCode1
A2C is a special case of PPOCode1
Decision Transformer: Reinforcement Learning via Sequence ModelingCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
Deep Actor-Critic Learning for Distributed Power Control in Wireless Mobile NetworksCode1
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative ExplorationCode1
Asynchronous Reinforcement Learning for Real-Time Control of Physical RobotsCode1
Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement LearningCode1
Asynchronous Methods for Deep Reinforcement LearningCode1
Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value FunctionCode1
Decentralized Deep Reinforcement Learning for a Distributed and Adaptive Locomotion Controller of a Hexapod RobotCode1
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement LearningCode1
A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement LearningCode1
A SWAT-based Reinforcement Learning Framework for Crop ManagementCode1
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline GenerationCode1
6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement LearningCode1
Debiased Contrastive LearningCode1
Deceptive Path Planning via Reinforcement Learning with Graph Neural NetworksCode1
Deep Black-Box Reinforcement Learning with Movement PrimitivesCode1
Deep Reinforcement Learning for Active Human Pose EstimationCode1
Deep RL Agent for a Real-Time Action Strategy GameCode1
DMC-VB: A Benchmark for Representation Learning for Control with Visual DistractorsCode1
Asset Allocation: From Markowitz to Deep Reinforcement LearningCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain AdaptationCode1
D2RL: Deep Dense Architectures in Reinforcement LearningCode1
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Benchmark Results

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