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
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...
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,...
This demonstration illustrates the feasibility of harvesting data from a WSN by interested parties, either in the WSN coverage area or in a remote location. Embedded and mobile ag...
Richard Tynan, Conor Muldoon, Michael J. O'Grady, ...
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