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 5851–5875 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
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Benchmark Results

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