We consider the problem of providing network access to hosts whose physical location changes with time. Such hosts cannot depend on traditional forms of network connectivity and r...
John Ioannidis, Dan Duchamp, Gerald Q. Maguire Jr.
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
Many real-world tasks can be decomposed into pipelines of sequential operations (where subtasks may themselves be composed of one or more pipelines). JGram is a framework enabling...
Rahul Sukthankar, Antoine Brusseau, Ray Pelletier,...
Human Learning on the Grid will be based on the synergies between advanced software and Human agents. These synergies will be possible to the extent that conversational protocols ...
Stefano A. Cerri, Marc Eisenstadt, Clement Jonquet
Communication in open heterogeneous multi agent systems is hampered by lack of shared ontologies. To overcome these problems, we propose a layered communication protocol which inc...
Jurriaan van Diggelen, Robbert-Jan Beun, Frank Dig...