We propose extrinsic and intrinsic deep neural network architectures as
...
In this paper, we investigate the architecture of an optimal controller ...
We study the problem of learning decentralized linear quadratic regulato...
In decentralized cooperative multi-agent reinforcement learning, agents ...
Numerical solution of partial differential equations on parallel compute...
Adversarial examples can easily degrade the classification performance i...
This paper considers a novel multi-agent linear stochastic approximation...
Adversarial attacks during training can strongly influence the performan...
Fictitious play is a popular learning algorithm in which players that ut...
In applications such as participatory sensing and crowd sensing,
self-in...
Communication in parallel systems imposes significant overhead which oft...
Recently, many cooperative distributed multi-agent reinforcement learnin...
We study a setting in which a principal selects an agent to execute a
co...
This technical note investigates the minimum average transmit power requ...
Consider a group of nodes aiming to solve a resource allocation problem
...
In this paper, we consider a general distributed system with multiple ag...
The intermittent nature of the renewable energies increases the operatio...
This paper presents a multi-stage approach to the placement of charging
...
This paper studies the problem of multi-stage placement of electric vehi...
The main goal of this study is to extract a set of brain networks in mul...