Title :
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
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;
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
DOI :
10.1109/WI-IAT.2012.250
