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Evolving classification of agents' behaviours : a general approach.

Iglesias, Jose Antonio and Angelov, Plamen and Ledezma, Agapito and Sanchis, Araceli (2010) Evolving classification of agents' behaviours : a general approach. Evolving Systems, 1 (3). pp. 161-171. ISSN 1868-6478

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Abstract

By recognizing the behavior of others, many different tasks can be performed, such as to predict their future behavior, to coordinate with them or to assist them. If this behavior recognition can be done automatically, it can be very useful in many applications. However, an agents’ behavior is not necessarily fixed but rather it evolves/changes. Thus, it is essential to take into account these changes in any behavior recognition system. In this paper, we present a general approach to the classification of streaming data which represent a specific agent behavior based on evolving systems. The experiment results show that an evolving system based on our approach can efficiently model and recognize different behaviors in very different domains, in particular, UNIX command-line data streams, and intelligent home environments. (c) Springer

Item Type: Article
Journal or Publication Title: Evolving Systems
Uncontrolled Keywords: Evolving fuzzy systems ; Agent modeling ; Behavior classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 34352
Deposited By: Dr. Plamen Angelov
Deposited On: 08 Oct 2010 18:27
Refereed?: Yes
Published?: Published
Last Modified: 03 Jun 2014 16:46
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/34352

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