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dc.contributor.authorKasabov, N
dc.date.accessioned2014-03-21T00:41:44Z
dc.date.available2014-03-21T00:41:44Z
dc.date.copyright2014
dc.date.issued2014-03-21
dc.identifier.citationSpringer Handbook of Bio-/Neuroinformatics (2014), pp 1083-1098
dc.identifier.isbn978-3-642-30573-3
dc.identifier.urihttp://hdl.handle.net/10292/6991
dc.description.abstractThis chapter discusses opportunities and challenges for the creation of methods of computational intelligence (CI) and more specifically – artificial neural networks (ANN), inspired by principles at different levels of information processing in the brain: cognitive, neuronal, genetic, and quantum, and mainly, the issues related to the integration of these principles into more powerful and accurate CI methods. It is demonstrated how some of these methods can be applied to model biological processes and to improve our understanding in the subject area; generic CI methods being applicable to challenging generic AI problems. The chapter first offers a brief presentation of some principles of information processing at different levels of the brain and then presents brain inspired, gene inspired, and quantum inspired CI. The main contribution of the chapter, however, is the introduction of methods inspired by the integration of principles from several levels of information processing, namely: A computational neurogenetic model that in one model combines gene information related to spiking neuronal activities. A general framework of a quantum spiking neural network (SNN) model. A general framework of a quantum computational neurogenetic model (CNGM). Many open questions and challenges are discussed, along with directions for further research.
dc.publisherSpringer-Verlag
dc.relation.urihttp://dx.doi.org/10.1007/978-3-642-30574-0_60
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.titleBrain, gene, and quantum inspired computational intelligence
dc.typeChapter in Book
dc.rights.accessrightsOpenAccess
dc.identifier.doi10.1007/978-3-642-30574-0
aut.publication.placeBerlin
aut.relation.chapternumber60
aut.relation.endpage1098
aut.relation.pages16
aut.relation.startpage1083
pubs.elements-id149091


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