RT Journal Article
T1 Evolving classification of agents’ behaviors: a general approach
A1 Iglesias Martínez, José Antonio
A1 Angelov, Plamen
A1 Ledezma Espino, Agapito Ismael
A1 Sanchis de Miguel, María Araceli
AB 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.
PB Springer
SN 1868-6478 (print)
SN 1868-6486 (online)
YR 2010
FD 2010-10
LK https://hdl.handle.net/10016/10471
UL https://hdl.handle.net/10016/10471
LA eng
NO This work has been partially supported by theSpanish Government under project TRA2007-67374-C02-02.
DS e-Archivo
RD 20 may. 2024