Investigating the evolution and stability of a resource limited artificial immune system.


Autoria(s): Timmis, John; Neal, Mark
Contribuinte(s)

Department of Computer Science

Intelligent Robotics Group

Data(s)

30/03/2006

30/03/2006

2000

Resumo

Timmis J and Neal M J. Investigating the evolution and stability of a resource limited artificial immune system. In Proceedings of GECCO - special workshop on artificial immune systems, pages 40-41. AAAI press, 2000.

This paper presents a resource limited artificial immune system for data analysis. The work presented here builds upon previous work on artificial immune systems for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learning algo- rithm. The new algorithm is presented, along with the immunological metaphors used as inspiration. Results are presented for the Fisher Iris data set, where very successful results are obtained in identifying clusters within the data set. It is argued that this new resource based mechanism is a large step forward in making artificial immune systems a viable contender for effective unsupervised machine learning and allows for not just a one shot learning mechanism, but a continual learning model to be developed.

Non peer reviewed

Formato

2

Identificador

Timmis , J & Neal , M 2000 , ' Investigating the evolution and stability of a resource limited artificial immune system. ' pp. 40-41 .

PURE: 67276

PURE UUID: d08c18b8-4901-4569-8726-060be1210265

dspace: 2160/87

http://hdl.handle.net/2160/87

Idioma(s)

eng

Tipo

/dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/other

Relação

Direitos