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 10101–10125 of 15113 papers

TitleStatusHype
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning—0
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning—0
NANCY: Neural Adaptive Network Coding methodologY for video distribution over wireless networks—0
Resource Allocation in Disaggregated Data Centre Systems with Reinforcement Learning—0
NaRLE: Natural Language Models using Reinforcement Learning with Emotion Feedback—0
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator—0
Natural Gradient Deep Q-learning—0
Natural Language-conditioned Reinforcement Learning with Inside-out Task Language Development and Translation—0
Natural Language Generation as Planning under Uncertainty Using Reinforcement Learning—0
Natural Language Person Search Using Deep Reinforcement Learning—0
Natural Language Reinforcement Learning—0
Language is Power: Representing States Using Natural Language in Reinforcement Learning—0
Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning—0
Natural Policy Gradient for Average Reward Non-Stationary RL—0
Natural Policy Gradients In Reinforcement Learning Explained—0
Natural Value Approximators: Learning when to Trust Past Estimates—0
NavBench: A Unified Robotics Benchmark for Reinforcement Learning-Based Autonomous Navigation—0
Navigating Assistance System for Quadcopter with Deep Reinforcement Learning—0
Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning—0
Navigating Uncertainty in ESG Investing—0
Navigating WebAI: Training Agents to Complete Web Tasks with Large Language Models and Reinforcement Learning—0
Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation—0
Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning—0
NavigationNet: A Large-scale Interactive Indoor Navigation Dataset—0
Navigation of micro-robot swarms for targeted delivery using reinforcement learning—0
Show:102550
← PrevPage 405 of 605Next →

Benchmark Results

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