Title :
Distributed mining of the Internet for novel news: evolutionary community of news foragers
Author :
Palotai, Zsolt ; Mandusitz, Sándor ; Lorincz, András
Author_Institution :
Dept. of Inf. Syst., Eotvos Lorand Univ., Budapest, Hungary
Abstract :
We populated a huge scale-free portion of Internet environment with news foragers. They evolved by a simple internal selective algorithm: selection concerned the memory components, being finite in size and containing the list of most promising supplies. Foragers received reward for locating not yet found news and used value estimation. Foragers were allowed to multiply if they passed a given productivity threshold. A particular property of this community is that there is no direct interaction (here, communication) amongst foragers. It is found that, still, fast compartmentalization, i.e., fast division of work can be achieved.
Keywords :
Internet; data mining; information resources; Internet; distributed mining; internal selective algorithm; memory components; news foragers; productivity threshold; value estimation; Artificial intelligence; Communication system control; Information systems; Intelligent agent; Intelligent robots; Internet; Learning; Particle swarm optimization; Uniform resource locators; World Wide Web;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380166
