Evolving intelligent system

Evolving Intelligent Systems (eIS) can be defined as self-developing, self-learning systems that have both their parameters but also (more importantly) their structure self-adapting on-line. They are usually (but not necessarily) based on fuzzy rule-based or neuro-fuzzy sysytems. Alternative frameworks are Hidden Markov Models, [structures], etc. This emerging area of research is still under intensive development.

EIS are usually associated with streaming data and on-line (often real-time) modes of operation. In a narrower sense they can be seen as adaptive intelligent systems. The difference is that eIS assume on-line adaptation of system structure in addition to the parameter adaptation which is usually associated with the term adaptive. They also allow for adaptation of the learning mechanism. Therefore, evolving assumes a higher level of adaptation.

In this definition the word evolving is used with its core meaning in English as described in the Oxford dictionary (Hornby, 1974; p. 294), namely unfolding; developing; being developed, naturally and gradually.

Often evolving is used in relation to evolutionary computation or genetic algorithms. The meaning of the term evolutionary is defined in the Oxford dictionary as development of more complicated forms of life (plants, animals) from earlier and simpler forms. EIS consider a gradual development of the underlying system structure and do not deal with such phenomena specific for the evolutionary computation or genetic algorithms as chromosomes crossover, mutation, selection and reproduction, parents and off-springs.

References

P. Angelov, D. Filev and N. Kasabov (Eds.), Evolving Intelligent Systems: Methodology and Applications, 444pp., John Willey and Sons, IEEE Press Series on Computational Intelligence, April 2010, ISBN 978-0-470-28719-4

P.P. Angelov, N. Kasabov. Evolving Computational Intelligence Systems. In Proceedings of the 1st International Workshop on Genetic Fuzzy Systems. Granada, Spain. 2005, pp. 76–82

P. Angelov, N. Kasabov, Evolving Intelligent Systems, eIS, IEEE SMC eNewsLetter, June 2006, pp. 1–13