Abstract- Multiagent reinforcement learning for multirobot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theor...
— Direct human control of multi-robot systems is limited by the cognitive ability of humans to coordinate numerous interacting components. In remote environments, such as those e...
Jeff G. Schneider, David Apfelbaum, Drew Bagnell, ...
— This paper presents an adaptive causal model method (adaptive CMM) for fault diagnosis and recovery in complex multi-robot teams. We claim that a causal model approach is effec...
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...