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 4026–4050 of 15113 papers

TitleStatusHype
Structured Reinforcement Learning for Delay-Optimal Data Transmission in Dense mmWave Networks—0
GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL—0
ActiveRIR: Active Audio-Visual Exploration for Acoustic Environment Modeling—0
DPO: A Differential and Pointwise Control Approach to Reinforcement Learning—0
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models—0
Impedance Matching: Enabling an RL-Based Running Jump in a Quadruped Robot—0
Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem—0
Planning the path with Reinforcement Learning: Optimal Robot Motion Planning in RoboCup Small Size League EnvironmentsCode0
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical SystemsCode0
Multi-view Disentanglement for Reinforcement Learning with Multiple CamerasCode0
Explicit Lipschitz Value Estimation Enhances Policy Robustness Against Perturbation—0
Fairness Incentives in Response to Unfair Dynamic Pricing—0
Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories—0
An Offline Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems—0
Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty—0
Data-Incremental Continual Offline Reinforcement Learning—0
Reinforcement Learning Approach for Integrating Compressed Contexts into Knowledge Graphs—0
TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning AgentsCode0
Actor-Critic Reinforcement Learning with Phased Actor—0
LTL-Constrained Policy Optimization with Cycle Experience Replay—0
Learn to Tour: Operator Design For Solution Feasibility Mapping in Pickup-and-delivery Traveling Salesman Problem—0
Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding—0
Physics-informed Actor-Critic for Coordination of Virtual Inertia from Power Distribution Systems—0
Achieving Constant Regret in Linear Markov Decision Processes—0
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning—0
Show:102550
← PrevPage 162 of 605Next →

Benchmark Results

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