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
Full text not available from this repository.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: | 26 Jul 2012 17:36 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/34352 |
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