NAISS
SUPR
NAISS Projects
SUPR
Learning based algorithm development for stochastic systems
Dnr:

NAISS 2026/4-1872

Type:

NAISS Small

Principal Investigator:

Arunava Naha

Affiliation:

Linköpings universitet

Start Date:

2026-10-15

End Date:

2027-11-01

Primary Classification:

20202: Control Engineering

Webpage:

Allocation

Abstract

I am currently working on two different problems, both of which require intensive computations, with additional GPU support being a valuable resource. The first problem involves communication efficient federated reinforcement learning (RL) and the second problem is on the study of offline RL. To support our study, we need to conduct extensive simulation studies for both problems. While the computations are both CPU and gpu-intensive. We will utilize neural networks in our models, which may benefit from additional GPU resources. Additionally, we will need to leverage multiple CPU cores in parallel.