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 5701–5750 of 15113 papers

TitleStatusHype
Few-Shot Preference Learning for Human-in-the-Loop RL—0
Adaptive Risk-Aware Bidding with Budget Constraint in Display AdvertisingCode0
A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks—0
Active Classification of Moving Targets with Learned Control Policies—0
A Learned Simulation Environment to Model Plant Growth in Indoor Farming—0
Efficient Learning of Voltage Control Strategies via Model-based Deep Reinforcement Learning—0
L2SR: Learning to Sample and Reconstruct for Accelerated MRI via Reinforcement LearningCode0
Robust Reinforcement Learning for Risk-Sensitive Linear Quadratic Gaussian Control—0
E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance—0
A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat—0
A Machine with Short-Term, Episodic, and Semantic Memory SystemsCode0
Bi-Level Optimization Augmented with Conditional Variational Autoencoder for Autonomous Driving in Dense Traffic—0
Differentiated Federated Reinforcement Learning Based Traffic Offloading on Space-Air-Ground Integrated Networks—0
Benchmarking Offline Reinforcement Learning Algorithms for E-Commerce Order Fraud Evaluation—0
Accelerating Interactive Human-like Manipulation Learning with GPU-based Simulation and High-quality Demonstrations—0
PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks—0
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed DatasetsCode0
Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search under Trajectory-based Guidance—0
Online Shielding for Reinforcement Learning—0
Automata Learning meets ShieldingCode0
DACOM: Learning Delay-Aware Communication for Multi-Agent Reinforcement Learning—0
Constrained Reinforcement Learning via Dissipative Saddle Flow Dynamics—0
Reinforcement learning with Demonstrations from Mismatched Task under Sparse Reward—0
Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning—0
On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning—0
STL-Based Synthesis of Feedback Controllers Using Reinforcement LearningCode0
Selecting Mechanical Parameters of a Monopode Jumping System with Reinforcement Learning—0
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems—0
CT-DQN: Control-Tutored Deep Reinforcement Learning—0
Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery—0
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox—0
Five Properties of Specific Curiosity You Didn't Know Curious Machines Should Have—0
Launchpad: Learning to Schedule Using Offline and Online RL Methods—0
Kick-motion Training with DQN in AI Soccer Environment—0
Online Learning-based Waveform Selection for Improved Vehicle Recognition in Automotive Radar—0
Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Merging—0
Modeling Mobile Health Users as Reinforcement Learning Agents—0
Reward Function Optimization of a Deep Reinforcement Learning Collision Avoidance System—0
Policy Optimization over General State and Action Spaces—0
Targets in Reinforcement Learning to solve Stackelberg Security Games—0
Reinforcement Learning for Multi-Truck Vehicle Routing Problems—0
Safe and Efficient Reinforcement Learning Using Disturbance-Observer-Based Control Barrier Functions—0
Random Copolymer inverse design system orienting on Accurate discovering of Antimicrobial peptide-mimetic copolymers—0
KRLS: Improving End-to-End Response Generation in Task Oriented Dialog with Reinforced Keywords LearningCode0
Funnel-based Reward Shaping for Signal Temporal Logic Tasks in Reinforcement Learning—0
Welfare and Fairness in Multi-objective Reinforcement LearningCode0
General policy mapping: online continual reinforcement learning inspired on the insect brainCode0
Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules—0
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning—0
Automatic Discovery of Multi-perspective Process Model using Reinforcement Learning—0
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Benchmark Results

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