Título: Trading off impact and mutation of knowledge by cooperatively learning robots
Autores: Richert, Willi
Kleinjohann, Bernd
Kleinjohann, Lisa
Fecha: 2012-11-12
2006-08
2006-08
Publicador: Unversidad Nacional de La Plata
Fuente:

Tipo: Objeto de conferencia
Objeto de conferencia
Tema: Robotics
Collaborative learning
Multiagent systems
Ciencias Informáticas
Descripción: We present a socially inspired approach that allows agents in Multi-Agent Systems to speed up their own learning process through communication. Thereby, they are able to trade off impact of knowledge by mutation dependent on the recent performance of the interacting agents. This is inspired by social interaction of humans, where the opinions of experts have greater impact on the overall opinion and are incorporated more exactly than those of newbies. The approach is successfully evaluated in a simulation in which mobile robots have to accomplish a task while taking care of timely recharging their resources
1st IFIP International Conference on Biologically Inspired Cooperative Computing - Robotics and Sensor Networks
Idioma: Inglés