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 8126–8150 of 15113 papers

TitleStatusHype
How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning AgentsCode0
Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model—0
Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
Bad-Policy Density: A Measure of Reinforcement Learning Hardness—0
Designing Composites with Target Effective Young's Modulus using Reinforcement Learning—0
Reinforcement Learning in Reward-Mixing MDPs—0
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning—0
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations—0
Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver—0
Optimized Recommender Systems with Deep Reinforcement LearningCode0
Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations—0
Pretraining & Reinforcement Learning: Sharpening the Axe Before Cutting the Tree—0
Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling under Data Governance—0
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers—0
Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning—0
Hierarchical Potential-based Reward Shaping from Task SpecificationsCode0
Adaptive control of a mechatronic system using constrained residual reinforcement learning—0
Learning Multi-Objective Curricula for Robotic Policy LearningCode0
A Deep Reinforcement Learning Framework for Contention-Based Spectrum Sharing—0
Deep reinforcement learning for guidewire navigation in coronary artery phantom—0
A study of first-passage time minimization via Q-learning in heated gridworlds—0
DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing—0
Decentralized Cooperative Lane Changing at Freeway Weaving Areas Using Multi-Agent Deep Reinforcement Learning—0
OTTR: Off-Road Trajectory Tracking using Reinforcement Learning—0
Show:102550
← PrevPage 326 of 605Next →

Benchmark Results

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