The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
Fuente:
arXiv
Saved in:
| Main Authors: | Scully, Ziv, Terenin, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
When Does the Gittins Policy Have Asymptotically Optimal Response Time Tail?
by: Scully, Ziv, et al.
Published: (2021)
by: Scully, Ziv, et al.
Published: (2021)
Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach
by: Alahyane, Abdelkrim, et al.
Published: (2026)
by: Alahyane, Abdelkrim, et al.
Published: (2026)
Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Between Model-Parameter Staleness and Update Frequency
by: Alahyane, Abdelkrim, et al.
Published: (2025)
by: Alahyane, Abdelkrim, et al.
Published: (2025)
Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability
by: Comte, Céline, et al.
Published: (2023)
by: Comte, Céline, et al.
Published: (2023)
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
by: Xie, Qian, et al.
Published: (2024)
by: Xie, Qian, et al.
Published: (2024)
Efficient Solving of Large Single Input Superstate Decomposable Markovian Decision Process
by: Mahjoub, Youssef Ait El, et al.
Published: (2025)
by: Mahjoub, Youssef Ait El, et al.
Published: (2025)
Strongly Tail-Optimal Scheduling in the Light-Tailed M/G/1
by: Yu, George, et al.
Published: (2024)
by: Yu, George, et al.
Published: (2024)
Tabular and Deep Reinforcement Learning for Gittins Index
by: Dhankhar, Harshit, et al.
Published: (2024)
by: Dhankhar, Harshit, et al.
Published: (2024)
Priority Scheduling in the M/G/1 with Preemption Overhead
by: Ramakrishna, Shefali, et al.
Published: (2026)
by: Ramakrishna, Shefali, et al.
Published: (2026)
Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty
by: Neufeld, Ariel, et al.
Published: (2022)
by: Neufeld, Ariel, et al.
Published: (2022)
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise
by: Agrawal, Shubhada, et al.
Published: (2026)
by: Agrawal, Shubhada, et al.
Published: (2026)
Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
by: Huynh, Phuoc-Toan, et al.
Published: (2026)
by: Huynh, Phuoc-Toan, et al.
Published: (2026)
Queues with resetting: a perspective
by: Roy, Reshmi, et al.
Published: (2024)
by: Roy, Reshmi, et al.
Published: (2024)
Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks
by: Dai, Yan, et al.
Published: (2024)
by: Dai, Yan, et al.
Published: (2024)
Control of parallel non-observable queues: asymptotic equivalence and optimality of periodic policies
by: Anselmi, Jonatha, et al.
Published: (2014)
by: Anselmi, Jonatha, et al.
Published: (2014)
Decision-Focused Bias Correction for Fluid Approximation
by: Er, Can, et al.
Published: (2025)
by: Er, Can, et al.
Published: (2025)
Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
by: Srinivasan, Vishwak, et al.
Published: (2025)
by: Srinivasan, Vishwak, et al.
Published: (2025)
Lagrangian Index Policy for Restless Bandits with Average Reward
by: Avrachenkov, Konstantin, et al.
Published: (2024)
by: Avrachenkov, Konstantin, et al.
Published: (2024)
Q-Learning under Finite Model Uncertainty
by: Sester, Julian, et al.
Published: (2024)
by: Sester, Julian, et al.
Published: (2024)
A Distributional View of High Dimensional Optimization
by: Benning, Felix
Published: (2025)
by: Benning, Felix
Published: (2025)
A Generalization Result for Convergence in Learning-to-Optimize
by: Sucker, Michael, et al.
Published: (2024)
by: Sucker, Michael, et al.
Published: (2024)
A stochastic gradient descent algorithm with random search directions
by: Gbaguidi, Eméric
Published: (2025)
by: Gbaguidi, Eméric
Published: (2025)
A Fisher-Rao gradient flow for entropic mean-field min-max games
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
When Machine Learning Meets Importance Sampling: A More Efficient Rare Event Estimation Approach
by: Zhao, Ruoning, et al.
Published: (2025)
by: Zhao, Ruoning, et al.
Published: (2025)
A Survey of Contextual Optimization Methods for Decision Making under Uncertainty
by: Sadana, Utsav, et al.
Published: (2023)
by: Sadana, Utsav, et al.
Published: (2023)
Asymptotic Optimality in Data-Driven Decision Making
by: Salač, Radek, et al.
Published: (2025)
by: Salač, Radek, et al.
Published: (2025)
Model Predictive Control is almost Optimal for Heterogeneous Restless Multi-armed Bandits
by: Narasimha, Dheeraj, et al.
Published: (2025)
by: Narasimha, Dheeraj, et al.
Published: (2025)
Non-convex entropic mean-field optimization via Best Response flow
by: Lascu, Razvan-Andrei, et al.
Published: (2025)
by: Lascu, Razvan-Andrei, et al.
Published: (2025)
ODE approximation for the Adam algorithm: General and overparametrized setting
by: Dereich, Steffen, et al.
Published: (2025)
by: Dereich, Steffen, et al.
Published: (2025)
Flatness-Aware Stochastic Gradient Langevin Dynamics
by: Bruno, Stefano, et al.
Published: (2025)
by: Bruno, Stefano, et al.
Published: (2025)
Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning
by: Comte, Céline, et al.
Published: (2025)
by: Comte, Céline, et al.
Published: (2025)
Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
by: Kassing, Sebastian, et al.
Published: (2025)
by: Kassing, Sebastian, et al.
Published: (2025)
Representative Action Selection for Large Action Space Bandit Families
by: Zhou, Quan, et al.
Published: (2025)
by: Zhou, Quan, et al.
Published: (2025)
Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers
by: Crafts, Evan Scope, et al.
Published: (2025)
by: Crafts, Evan Scope, et al.
Published: (2025)
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)
by: Dang, Thanh, et al.
Published: (2025)
Reinforcement Learning with Random Time Horizons
by: Borrell, Enric Ribera, et al.
Published: (2025)
by: Borrell, Enric Ribera, et al.
Published: (2025)
Representative Action Selection for Large Action Space: From Bandits to MDPs
by: Zhou, Quan, et al.
Published: (2025)
by: Zhou, Quan, et al.
Published: (2025)
Convergence of Actor-Critic Learning for Mean Field Games and Mean Field Control in Continuous Spaces
by: Fouque, Jean-Pierre, et al.
Published: (2025)
by: Fouque, Jean-Pierre, et al.
Published: (2025)
Improved Approximation Algorithms for Orthogonally Constrained Problems Using Semidefinite Optimization
by: Cory-Wright, Ryan, et al.
Published: (2025)
by: Cory-Wright, Ryan, et al.
Published: (2025)
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
by: Bruno, Stefano, et al.
Published: (2025)
by: Bruno, Stefano, et al.
Published: (2025)
Similar Items
-
When Does the Gittins Policy Have Asymptotically Optimal Response Time Tail?
by: Scully, Ziv, et al.
Published: (2021) -
Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach
by: Alahyane, Abdelkrim, et al.
Published: (2026) -
Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Between Model-Parameter Staleness and Update Frequency
by: Alahyane, Abdelkrim, et al.
Published: (2025) -
Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability
by: Comte, Céline, et al.
Published: (2023) -
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
by: Xie, Qian, et al.
Published: (2024)