This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
The increasing ubiquity of mobile computing devices has made mobile ad hoc networks an everyday occurrence. Applications in these networks are commonly structured as a logical netw...
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...
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...