SOTAVerified

Q-Learning

The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 626–650 of 1918 papers

TitleStatusHype
Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation—0
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement LearningCode1
Minimizing the Outage Probability in a Markov Decision Process—0
A Finite Sample Complexity Bound for Distributionally Robust Q-learning—0
Q-Cogni: An Integrated Causal Reinforcement Learning Framework—0
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation—0
On Bellman's principle of optimality and Reinforcement learning for safety-constrained Markov decision process—0
Robust Auto-landing Control of an agile Regional Jet Using Fuzzy Q-learning—0
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes—0
Learning to Play Text-based Adventure Games with Maximum Entropy Reinforcement LearningCode0
Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods—0
Logit-Q Dynamics for Efficient Learning in Stochastic Teams—0
Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications—0
Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data—0
Computation Offloading for Uncertain Marine Tasks by Cooperation of UAVs and Vessels—0
A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning—0
Differentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading—0
MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework—0
Catch Me If You Can: Improving Adversaries in Cyber-Security With Q-Learning Algorithms—0
Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage—0
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition—0
Best Possible Q-Learning—0
Sample Complexity of Kernel-Based Q-Learning—0
Analyzing Robustness of the Deep Reinforcement Learning Algorithm in Ramp Metering Applications Considering False Data Injection Attack and Defense—0
RCsearcher: Reaction Center Identification in Retrosynthesis via Deep Q-Learning—0
Show:102550
← PrevPage 26 of 77Next →

No leaderboard results yet.