113 citations · 290 across the 22 of their papers we have counts for
5 papers · 1 filter
Multi-Agent Reinforcement Learning for Long-Term Network Resource Allocation through Auction: a V2X Application
Jing Tan, Ramin Khalili, Holger Karl +1
We formulate offloading of computational tasks from a dynamic group of mobile agents (e.g., cars) as decentralized decision making among autonomous agents. We design an interaction…
Scheduling Out-of-Coverage Vehicular Communications Using Reinforcement Learning
Taylan Şahin, Ramin Khalili, Mate Boban +1
Performance of vehicle-to-vehicle (V2V) communications depends highly on the employed scheduling approach. While centralized network schedulers offer high V2V communication reliabi…
Learning to Bid Long-Term: Multi-Agent Reinforcement Learning with Long-Term and Sparse Reward in Repeated Auction Games
Jing Tan, Ramin Khalili, Holger Karl
We propose a multi-agent distributed reinforcement learning algorithm that balances between potentially conflicting short-term reward and sparse, delayed long-term reward, and lear…
Multi-Agent Distributed Reinforcement Learning for Making Decentralized Offloading Decisions
Jing Tan, Ramin Khalili, Holger Karl +1
We formulate computation offloading as a decentralized decision-making problem with autonomous agents. We design an interaction mechanism that incentivizes agents to align private…
CoCoFL: Communication- and Computation-Aware Federated Learning via Partial NN Freezing and Quantization
Kilian Pfeiffer, Martin Rapp, Ramin Khalili +1
Devices participating in federated learning (FL) typically have heterogeneous communication, computation, and memory resources. However, in synchronous FL, all devices need to fini…