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 10526–10550 of 15113 papers

TitleStatusHype
Batch Value-function Approximation with Only RealizabilityCode0
Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey—0
GRIMGEP: Learning Progress for Robust Goal Sampling in Visual Deep Reinforcement Learning—0
Deep Reinforcement Learning with Label Embedding Reward for Supervised Image Hashing—0
Fault-Tolerant Control of Degrading Systems with On-Policy Reinforcement Learning—0
Comparison of Model Predictive and Reinforcement Learning Methods for Fault Tolerant Control—0
Hierarchical Reinforcement Learning in StarCraft II with Human Expertise in Subgoals Selection—0
Distributed Deep Reinforcement Learning for Functional Split Control in Energy Harvesting Virtualized Small Cells—0
A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning—0
Incremental Text to Speech for Neural Sequence-to-Sequence Models using Reinforcement Learning—0
Towards Sample Efficient Agents through Algorithmic AlignmentCode0
Managing caching strategies for stream reasoning with reinforcement learning—0
Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning—0
Mixed-Initiative Level Design with RL BrushCode0
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion—0
Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents—0
A Gentle Lecture Note on Filtrations in Reinforcement Learning—0
Deep reinforcement learning to detect brain lesions on MRI: a proof-of-concept application of reinforcement learning to medical images—0
Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning—0
Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille KeyboardCode0
Area-wide traffic signal control based on a deep graph Q-Network (DGQN) trained in an asynchronous manner—0
Deep Reinforcement Learning for Field Development Optimization—0
Learning Power Control from a Fixed Batch of Data—0
Reinforcement Learning-driven Information Seeking: A Quantum Probabilistic Approach—0
Optimizing AD Pruning of Sponsored Search with Reinforcement Learning—0
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Benchmark Results

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