A Novel Meta Learning System and Its Application to Optimization of Computing Agents´ Results

Author

Kazik, Ondrej ; Pekovas, Klara ; Pilat, M. ; Neruda, Roman

Author_Institution

Dept. of Theor. Comput. Sci., Charles Univ. Prague, Prague, Czech Republic

Volume

2

fYear

2012

fDate

4-7 Dec. 2012

Firstpage

170

Lastpage

174

Abstract

We present a description of our multi-agent system where computational intelligence methods are embodied as software agents. This system is designed in order to allow easy experiments with learning, meta learning, gathering experience based on previous computations, and recommending suitable methods for particular data. The architecture of the system is presented and its meta learning abilities are demonstrated on a set of experiments with neural network models and both evolutionary and local search heuristics.

Keywords

learning (artificial intelligence); multi-agent systems; neural nets; optimisation; software agents; computational intelligence methods; computing agent results; evolutionary heuristics; local search heuristics; meta learning abilities; meta learning system; multiagent system; neural network models; optimization; software agents; data-mining; meta-learning; multi-agent system; ontology; roles;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on

Conference_Location

Macau

Print_ISBN

978-1-4673-6057-9

Type

conf

DOI

10.1109/WI-IAT.2012.250

Filename

6511567