Abstract—On-chip power density and temperature are rising exponentially with decreasing feature sizes. This alarming trend calls for temperature management at every level of syst...
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
We study three scheduling problems (file redistribution, independent tasks scheduling and broadcasting) on large scale heterogeneous platforms under the Bounded Multi-port Model. I...
We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
In set-system auctions, there are several overlapping teams of agents, and a task that can be completed by any of these teams. The auctioneer's goal is to hire a team and pay...
Edith Elkind, Leslie Ann Goldberg, Paul W. Goldber...