32 citations · 83 across the 10 of their papers we have counts for
11 papers
Deep reinforcement learning for weakly coupled MDP's with continuous actions
Francisco Robledo, Urtzi Ayesta, Konstantin Avrachenkov
This paper introduces the Lagrange Policy for Continuous Actions (LPCA), a reinforcement learning algorithm specifically designed for weakly coupled MDP problems with continuous ac…
Tabular and Deep Learning for the Whittle Index
Francisco Robledo Relaño, Vivek Borkar, Urtzi Ayesta +1
The Whittle index policy is a heuristic that has shown remarkably good performance (with guaranteed asymptotic optimality) when applied to the class of problems known as Restless M…
A Survey of Stability Results for Redundancy Systems
Elene Anton, Urtzi Ayesta, Matthieu Jonckheere +1
Redundancy mechanisms consist in sending several copies of a same job to a subset of servers. It constitutes one of the most promising ways to exploit diversity in multiservers app…
Improving the performance of heterogeneous data centers through redundancy
Elene Anton, Urtzi Ayesta, Matthieu Jonckheere +1
We analyze the performance of redundancy in a multi-type job and multi-type server system. We assume the job dispatcher is unaware of the servers' capacities, and we set out to stu…
A unifying computations of Whittle's Index for Markovian bandits
Urtzi Ayesta, Manu K. Gupta, Ina Maria Verloop
The multi-armed restless bandit framework allows to model a wide variety of decision-making problems in areas as diverse as industrial engineering, computer communication, operatio…
On the stability of redundancy models
E. Anton, U. Ayesta, M. Jonckheere +1
We investigate the stability condition of redundancy- multi-server systems. Each server has its own queue and implements popular scheduling disciplines such as First-Come-First-…