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 8101–8125 of 15113 papers

TitleStatusHype
Feeling of Presence Maximization: mmWave-Enabled Virtual Reality Meets Deep Reinforcement Learning—0
MICo: Improved representations via sampling-based state similarity for Markov decision processesCode0
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement LearningCode1
Hyperbolically-Discounted Reinforcement Learning on Reward-Punishment Framework—0
LiMIIRL: Lightweight Multiple-Intent Inverse Reinforcement Learning—0
Grounding Complex Navigational Instructions Using Scene Graphs—0
Towards Learning to Play Piano with Dexterous Hands and Touch—0
Offline Reinforcement Learning as One Big Sequence Modeling ProblemCode1
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement LearningCode0
Safe RAN control: A Symbolic Reinforcement Learning Approach—0
Robot in a China Shop: Using Reinforcement Learning for Location-Specific Navigation Behaviour—0
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning—0
Towards Deeper Deep Reinforcement Learning with Spectral Normalization—0
Design and Comparison of Reward Functions in Reinforcement Learning for Energy Management of Sensor Nodes—0
Learning to schedule job-shop problems: Representation and policy learning using graph neural network and reinforcement learning—0
Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making—0
Decision Transformer: Reinforcement Learning via Sequence ModelingCode1
Ad Headline Generation using Self-Critical Masked Language Model—0
Quantitative Day Trading from Natural Language using Reinforcement Learning—0
An Entropy Regularization Free Mechanism for Policy-based Reinforcement Learning—0
A Coarse to Fine Question Answering System based on Reinforcement Learning—0
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Reinforcement Learning—0
Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs—0
Reward is enough for convex MDPs—0
Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding—0
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Benchmark Results

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