Multi-Agent Reinforcement Learning for Long-Term Network Resource Allocation through Auction: a V2X Application

no code implementations • 29 Jul 2022 • Jing Tan, Ramin Khalili, Holger Karl, Artur Hecker

We formulate offloading of computational tasks from a dynamic group of mobile agents (e. g., cars) as decentralized decision making among autonomous agents.

Decision Making Fairness +1

Multi-Agent Distributed Reinforcement Learning for Making Decentralized Offloading Decisions

1 code implementation • 5 Apr 2022 • Jing Tan, Ramin Khalili, Holger Karl, Artur Hecker

We formulate computation offloading as a decentralized decision-making problem with autonomous agents.

Decision Making Fairness +2

Self-Driving Network and Service Coordination Using Deep Reinforcement Learning

1 code implementation • 2 Nov 2020 • Stefan Schneider, Adnan Manzoor, Haydar Qarawlus, Rafael Schellenberg, Holger Karl, Ramin Khalili, Artur Hecker

While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e. g., a priori knowledge).

reinforcement-learning Reinforcement Learning (RL)

Towards Runtime Verification of Programmable Switches

no code implementations • 22 Apr 2020 • Apoorv Shukla, Kevin Hudemann, Zsolt Vági, Lily Hügerich, Georgios Smaragdakis, Stefan Schmid, Artur Hecker, Anja Feldmann

Once the bug in a P4 program is localized, the faulty code can be patched due to the programmable nature of P4.