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 2501–2525 of 15113 papers

TitleStatusHype
A Comparative Study of AI-based Intrusion Detection Techniques in Critical Infrastructures—0
Avoiding Jammers: A Reinforcement Learning Approach—0
Avoiding Catastrophic States with Intrinsic Fear—0
Adaptive Reinforcement Learning for Unobservable Random Delays—0
A Benchmarking Environment for Reinforcement Learning Based Task Oriented Dialogue Management—0
Contrastive Unsupervised Learning of World Model with Invariant Causal Features—0
Avoidance Learning Using Observational Reinforcement Learning—0
A Visual Communication Map for Multi-Agent Deep Reinforcement Learning—0
A Model-Based Reinforcement Learning Approach for PID Design—0
A Vision Based Deep Reinforcement Learning Algorithm for UAV Obstacle Avoidance—0
A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task—0
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning—0
A comparative evaluation of machine learning methods for robot navigation through human crowds—0
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos—0
Average-Reward Reinforcement Learning with Entropy Regularization—0
A Model-based Multi-Agent Personalized Short-Video Recommender System—0
Average-Reward Reinforcement Learning with Trust Region Methods—0
Average Reward Reinforcement Learning with Monotonic Policy Improvement—0
A model-based approach to meta-Reinforcement Learning: Transformers and tree search—0
Adaptive Q-learning for Interaction-Limited Reinforcement Learning—0
Deep Reinforcement Learning Architecture for Continuous Power Allocation in High Throughput Satellites—0
Unknown mixing times in apprenticeship and reinforcement learning—0
Average Reward Reinforcement Learning for Omega-Regular and Mean-Payoff Objectives—0
A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning—0
Average Reward Reinforcement Learning for Wireless Radio Resource Management—0
Show:102550
← PrevPage 101 of 605Next →

Benchmark Results

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