21 citations · 24 across the 3 of their papers we have counts for
4 papers
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…
Distributed Learning on Heterogeneous Resource-Constrained Devices
Martin Rapp, Ramin Khalili, Jörg Henkel
We consider a distributed system, consisting of a heterogeneous set of devices, ranging from low-end to high-end. These devices have different profiles, e.g., different energy budg…
VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
Taylan Şahin, Ramin Khalili, Mate Boban +1
Vehicle-to-vehicle (V2V) communications have distinct challenges that need to be taken into account when scheduling the radio resources. Although centralized schedulers (e.g., loca…
Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Outside Coverage
Taylan Şahin, Ramin Khalili, Mate Boban +1
Radio resources in vehicle-to-vehicle (V2V) communication can be scheduled either by a centralized scheduler residing in the network (e.g., a base station in case of cellular syste…