- Evolving Systems Journal
- October 2010
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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.