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

Showing 77017750 of 15113 papers

TitleStatusHype
Specializing Versatile Skill Libraries using Local Mixture of ExpertsCode0
CoMPS: Continual Meta Policy Search0
Hyper-parameter optimization based on soft actor critic and hierarchical mixture regularization0
Application of Deep Reinforcement Learning to Payment Fraud0
Learning to Select the Next Reasonable Mention for Entity Linking0
Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System0
A Review for Deep Reinforcement Learning in Atari:Benchmarks, Challenges, and Solutions0
Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approach0
Deep Q-Learning Market Makers in a Multi-Agent Simulated Stock Market0
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning0
Attention-Based Model and Deep Reinforcement Learning for Distribution of Event Processing TasksCode0
A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules0
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach0
Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project0
QKSA: Quantum Knowledge Seeking Agent -- resource-optimized reinforcement learning using quantum process tomography0
Model-free Nearly Optimal Control of Constrained-Input Nonlinear Systems Based on Synchronous Reinforcement Learning0
MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance0
Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learning0
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning0
Virtual Replay CacheCode0
MDPFuzz: Testing Models Solving Markov Decision Processes0
MDPGT: Momentum-based Decentralized Policy Gradient TrackingCode0
Flexible Option LearningCode0
Lecture Notes on Partially Known MDPs0
Deep differentiable reinforcement learning and optimal trading0
Distilled Domain Randomization0
Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning0
Deep Policy Iteration with Integer Programming for Inventory Management0
Reinforcement learning for options on target volatility funds0
An Analytical Update Rule for General Policy Optimization0
Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning0
Differentially Private Exploration in Reinforcement Learning with Linear Representation0
Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems0
Convergence Guarantees for Deep Epsilon Greedy Policy Learning0
Architecting and Visualizing Deep Reinforcement Learning Models0
Towards Personalization of User Preferences in Partially Observable Smart Home Environments0
Maximum Entropy Model-based Reinforcement Learning0
A Generic Graph Sparsification Framework using Deep Reinforcement LearningCode0
Towards Interactive Reinforcement Learning with Intrinsic Feedback0
Reward-Free Attacks in Multi-Agent Reinforcement Learning0
Sample Complexity of Robust Reinforcement Learning with a Generative ModelCode0
Safe Reinforcement Learning for Grid Voltage Control0
Reinforcement Learning Enhanced Explainer for Graph Neural Networks0
Multi-Agent Transfer Learning in Reinforcement Learning-Based Ride-Sharing Systems0
Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision ProcessesCode0
DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement LearningCode0
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning0
On the Practical Consistency of Meta-Reinforcement Learning Algorithms0
Structural Credit Assignment in Neural Networks using Reinforcement Learning0
RMIX: Learning Risk-Sensitive Policies forCooperative Reinforcement Learning Agents0
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Benchmark Results

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