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 5851–5900 of 15113 papers

TitleStatusHype
AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection—0
Dynamic Dialogue Policy for Continual Reinforcement Learning—0
A Reinforcement Learning Approach for Electric Vehicle Routing Problem with Vehicle-to-Grid Supply—0
An Analysis of Discretization Methods for Communication Learning with Multi-Agent Reinforcement Learning—0
When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning?—0
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human FeedbackCode2
RL-CoSeg : A Novel Image Co-Segmentation Algorithm with Deep Reinforcement Learning—0
Forgetting and Imbalance in Robot Lifelong Learning with Off-policy Data—0
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning—0
External control of a genetic toggle switch via Reinforcement Learning—0
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios—0
Implementing Online Reinforcement Learning with Temporal Neural Networks—0
Deep Reinforcement Learning Based Semi-Autonomous Control for Robotic Surgery—0
JORLDY: a fully customizable open source framework for reinforcement learningCode2
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning—0
Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels—0
gTLO: A Generalized and Non-linear Multi-Objective Deep Reinforcement Learning ApproachCode0
Model-free optimization of power/efficiency tradeoffs in quantum thermal machines using reinforcement learningCode0
NeuRL: Closed-form Inverse Reinforcement Learning for Neural Decoding—0
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
A Spiking Neural Network Structure Implementing Reinforcement Learning—0
Hardware Trojan Insertion Using Reinforcement Learning—0
Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads—0
Evolving Pareto-Optimal Actor-Critic Algorithms for Generalizability and Stability—0
Approximate discounting-free policy evaluation from transient and recurrent states—0
Data-Driven Evaluation of Training Action Space for Reinforcement Learning—0
Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for RoboticsCode1
On Improving Cross-dataset Generalization of Deepfake Detectors—0
The Complexity of Markov Equilibrium in Stochastic Games—0
Semantic Exploration from Language Abstractions and Pretrained Representations—0
Q-learning with online random forests—0
Optimizing the Long-Term Behaviour of Deep Reinforcement Learning for Pushing and Grasping—0
Offline Reinforcement Learning for Safer Blood Glucose Control in People with Type 1 DiabetesCode1
Temporal Alignment for History Representation in Reinforcement LearningCode0
Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale—0
Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning—0
Distributed Reinforcement Learning for Robot Teams: A Review—0
Federated Reinforcement Learning with Environment HeterogeneityCode1
Standardized feature extraction from pairwise conflicts applied to the train rescheduling problem—0
On the Computational Consequences of Cost Function Design in Nonlinear Optimal Control—0
RL4ReAl: Reinforcement Learning for Register Allocation—0
Multi-Agent Distributed Reinforcement Learning for Making Decentralized Offloading DecisionsCode1
Learning to Bid Long-Term: Multi-Agent Reinforcement Learning with Long-Term and Sparse Reward in Repeated Auction GamesCode0
Inferring Rewards from Language in ContextCode1
Jump-Start Reinforcement LearningCode1
Configuration Path Control—0
Automating Reinforcement Learning with Example-based ResetsCode0
Reinforcement Learning Agents in Colonel BlottoCode0
Value Gradient weighted Model-Based Reinforcement LearningCode1
Optimising Energy Efficiency in UAV-Assisted Networks using Deep Reinforcement Learning—0
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Benchmark Results

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