Cooperative robotic networks for underwater surveillance: an overview

G Ferri*, A Munafò*, A Tesei, P Braca… - IET Radar, Sonar & …, 2017 - Wiley Online Library
Underwater surveillance has traditionally been carried out by means of surface and
undersea manned vessels equipped with advanced sensor systems. This approach is often …

A survey on cross-layer quality-of-service approaches in WSNs for delay and reliability-aware applications

I Al-Anbagi, M Erol-Kantarci… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Using wireless sensor networks (WSNs) in delay and reliability critical environments is
highly desired due to their unique advantages such as low cost, ease of deployment, and …

Diffusion LMS over multitask networks

J Chen, C Richard, AH Sayed - IEEE Transactions on Signal …, 2015 - ieeexplore.ieee.org
The diffusion LMS algorithm has been extensively studied in recent years. This efficient
strategy allows to address distributed optimization problems over networks in the case …

Optimal algorithms for multiplayer multi-armed bandits

PA Wang, A Proutiere, K Ariu… - International …, 2020 - proceedings.mlr.press
The paper addresses various Multiplayer Multi-Armed Bandit (MMAB) problems, where M
decision-makers, or players, collaborate to maximize their cumulative reward. We first …

Decentralized cooperative stochastic bandits

D Martínez-Rubio, V Kanade… - Advances in Neural …, 2019 - proceedings.neurips.cc
We study a decentralized cooperative stochastic multi-armed bandit problem with K arms on
a network of N agents. In our model, the reward distribution of each arm is the same for each …

Distributed detection over adaptive networks using diffusion adaptation

FS Cattivelli, AH Sayed - IEEE Transactions on Signal …, 2011 - ieeexplore.ieee.org
We study the problem of distributed detection, where a set of nodes is required to decide
between two hypotheses based on available measurements. We seek fully distributed and …

Distributed cooperative decision making in multi-agent multi-armed bandits

P Landgren, V Srivastava, NE Leonard - Automatica, 2021 - Elsevier
We study a distributed decision-making problem in which multiple agents face the same
multi-armed bandit (MAB), and each agent makes sequential choices among arms to …

Distributed cooperative decision-making in multiarmed bandits: Frequentist and bayesian algorithms

P Landgren, V Srivastava… - 2016 IEEE 55th …, 2016 - ieeexplore.ieee.org
We study distributed cooperative decision-making under the explore-exploit tradeoff in the
multiarmed bandit (MAB) problem. We extend state-of-the-art frequentist and Bayesian …

Distributed learning for stochastic generalized Nash equilibrium problems

CK Yu, M Van Der Schaar… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper examines a stochastic formulation of the generalized Nash equilibrium problem
where agents are subject to randomness in the environment of unknown statistical …

On distributed cooperative decision-making in multiarmed bandits

P Landgren, V Srivastava… - 2016 European Control …, 2016 - ieeexplore.ieee.org
We study the explore-exploit tradeoff in distributed cooperative decision-making using the
context of the multiarmed bandit (MAB) problem. For the distributed cooperative MAB …