Creator:

Czarnowski, Ireneusz ; Jędrzejowicz, Piotr

Contributor:

Korbicz, Józef - red. ; Uciński, Dariusz - red.

Title:

Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem

Group publication title:

AMCS, Volume 21 (2011)

Subject and Keywords:

data reduction ; machine learning ; A-Team ; optimization ; multi-agent system

Abstract:

The problem considered concerns data reduction for machine learning. Data reduction aims at deciding which features and instances from the training set should be retained for further use during the learning process. Data reduction results in increased capabilities and generalization properties of the learning model and a shorter time of the learning process. It can also help in scaling up to large data sources. The paper proposes an agent-based data reduction approach with the learning process executed by a team of agents (A-Team). Several A-Team architectures with agents executing the simulated annealing and tabu search procedures are proposed and investigated. The paper includes a detailed description of the proposed approach and discusses the results of a validating experiment.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2011

Resource Type:

artykuł

DOI:

10.2478/v10006-011-0004-3

Pages:

57-68

Source:

AMCS, Volume 21, Number 1 (2011) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego