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 7451–7500 of 15113 papers

TitleStatusHype
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning—0
Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point ProcessesCode0
DeepRNG: Towards Deep Reinforcement Learning-Assisted Generative Testing of Software—0
Explaining Reinforcement Learning Policies through Counterfactual TrajectoriesCode0
ApolloRL: a Reinforcement Learning Platform for Autonomous Driving—0
Zeroth-Order Actor-Critic: An Evolutionary Framework for Sequential Decision ProblemsCode0
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints—0
Overcoming Exploration: Deep Reinforcement Learning for Continuous Control in Cluttered Environments from Temporal Logic Specifications—0
Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methodsCode0
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise—0
Dynamic Temporal Reconciliation by Reinforcement learning—0
FCMNet: Full Communication Memory Net for Team-Level Cooperation in Multi-Agent SystemsCode0
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation—0
Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphs—0
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning—0
Modeling Human Exploration Through Resource-Rational Reinforcement LearningCode0
Generative Adversarial Exploration for Reinforcement Learning—0
Human-centered mechanism design with Democratic AI—0
The Challenges of Exploration for Offline Reinforcement Learning—0
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence—0
Boosting Exploration in Multi-Task Reinforcement Learning using Adversarial NetworksCode0
Quantile-Based Policy Optimization for Reinforcement Learning—0
Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center—0
Probe-Based Interventions for Modifying Agent Behavior—0
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes—0
Exploiting Semantic Epsilon Greedy Exploration Strategy in Multi-Agent Reinforcement Learning—0
Hyperparameter Tuning for Deep Reinforcement Learning Applications—0
Learning Invariable Semantical Representation from Language for Extensible Policy Generalization—0
Using Deep Reinforcement Learning for Zero Defect Smart Forging—0
MOORe: Model-based Offline-to-Online Reinforcement Learning—0
Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching—0
Accelerated Intravascular Ultrasound Imaging using Deep Reinforcement Learning—0
Generative Planning for Temporally Coordinated Exploration in Reinforcement LearningCode0
Large-Scale Graph Reinforcement Learning in Wireless Control Systems—0
State-Conditioned Adversarial Subgoal Generation—0
Understanding the Effects of Second-Order Approximations in Natural Policy Gradient Reinforcement LearningCode0
Online Attentive Kernel-Based Temporal Difference Learning—0
Multi-Agent Adversarial Attacks for Multi-Channel Communications—0
Reinforcement Learning Your Way: Agent Characterization through Policy Regularization—0
Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement LearningCode0
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search—0
Reinforcement Learning for Personalized Drug Discovery and Design for Complex Diseases: A Systems Pharmacology Perspective—0
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning—0
Deep Reinforcement Learning with Spiking Q-learning—0
Instance-Dependent Confidence and Early Stopping for Reinforcement Learning—0
Environment Generation for Zero-Shot Compositional Reinforcement Learning—0
Deep reinforcement learning under signal temporal logic constraints using Lagrangian relaxation—0
A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning—0
Self-Awareness Safety of Deep Reinforcement Learning in Road Traffic Junction Driving—0
Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning—0
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Benchmark Results

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