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

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Showing 5401–5450 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systems—0
Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocation—0
Developing Driving Strategies Efficiently: A Skill-Based Hierarchical Reinforcement Learning Approach—0
Online Reinforcement Learning in Non-Stationary Context-Driven EnvironmentsCode0
Reinforcement Learning in Low-Rank MDPs with Density Features—0
Reinforcement Learning with History-Dependent Dynamic Contexts—0
Reinforcing User Retention in a Billion Scale Short Video Recommender System—0
Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties—0
Deep Reinforcement Learning for Online Error Detection in Cyber-Physical Systems—0
Distributional constrained reinforcement learning for supply chain optimizationCode0
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints—0
Lower Bounds for Learning in Revealing POMDPs—0
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition—0
MARLIN: Soft Actor-Critic based Reinforcement Learning for Congestion Control in Real Networks—0
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs—0
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms—0
Sample Complexity of Kernel-Based Q-Learning—0
Multi-zone HVAC Control with Model-Based Deep Reinforcement Learning—0
Selective Uncertainty Propagation in Offline RL—0
Bridging Physics-Informed Neural Networks with Reinforcement Learning: Hamilton-Jacobi-Bellman Proximal Policy Optimization (HJBPPO)—0
QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing—0
Collaborating with language models for embodied reasoning—0
Combining Deep Reinforcement Learning and Search with Generative Models for Game-Theoretic Opponent Modeling—0
A Reinforcement Learning Framework for Dynamic Mediation AnalysisCode0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
CRC-RL: A Novel Visual Feature Representation Architecture for Unsupervised Reinforcement LearningCode0
Enabling surrogate-assisted evolutionary reinforcement learning via policy embedding—0
Towards interpretable quantum machine learning via single-photon quantum walks—0
Partitioning Distributed Compute Jobs with Reinforcement Learning and Graph Neural Networks—0
Scaling laws for single-agent reinforcement learning—0
Skill Decision TransformerCode0
Scalable Grid-Aware Dynamic Matching using Deep Reinforcement Learning—0
Scheduling Inference Workloads on Distributed Edge Clusters with Reinforcement Learning—0
Planning Multiple Epidemic Interventions with Reinforcement LearningCode0
STEEL: Singularity-aware Reinforcement Learning—0
V2N Service Scaling with Deep Reinforcement Learning—0
Identifying Expert Behavior in Offline Training Datasets Improves Behavioral Cloning of Robotic Manipulation PoliciesCode0
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents—0
PAC-Bayesian Soft Actor-Critic LearningCode0
Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem—0
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation—0
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement LearningCode0
Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs—0
A Deep Reinforcement Learning Framework for Optimizing Congestion Control in Data Centers—0
Autonomous Satellite Docking via Adaptive Optimal Output Rregulation: A Reinforcement Learning Approach—0
Sample Efficient Deep Reinforcement Learning via Local Planning—0
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning—0
Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning—0
SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning—0
Towards Learning Rubik's Cube with N-tuple-based Reinforcement Learning—0
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Benchmark Results

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