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2006-03-16Buch DOI: 10.18452/3786
A generic architecture for hybrid intelligent systems
dc.contributor.authorJacobsen, Hans-Arno
dc.date.accessioned2017-06-15T22:07:02Z
dc.date.available2017-06-15T22:07:02Z
dc.date.created2006-03-16
dc.date.issued2006-03-16none
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4438
dc.description.abstractThe integration of different learning and adaptation techniques in one architecture, to overcome individual limitations and achieve synergetic effects through hybridization or fusion of these techniques, has in recent years contributed to a large number of new intelligent system designs. Most of these approaches, however, follow an ad hoc design methodology, further justified by success in certain application domains. Due to the lack of a common framework it remains often difficult to compare the various systems conceptually and evaluate their performance comparatively. In this paper we first aim at classifying state-of-the-art intelligent systems, which have evolved over the past decade in the soft computing community. We identify four categories, based on the systems, overall architecture: (1) single component systems, (2) fusion-based systems, (3) hierarchical systems, and (4) hybrid systems. We then introduce a unifying paradigm, derived from concepts well known in the AI and agent community, as conceptual framework to better understand, modularize, compare and evaluate the individual approaches. We think it is crucial for the design of intelligent systems to focus on the integration and interaction of different learning techniques in one model rather then merging them to create ever new techniques. Two original instantiations of this framework are presented and discussed. Their performance is evaluated for prefetching of bulk data over wireless media.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.relation.ispartofseriesSonderforschungsbereich 373: Quantification and Simulation of Economic Processes - 113, SFB 373 Papers, ISSN:1436-1086
dc.subjectIntelligent systemseng
dc.subjectneuro-fuzzy approacheseng
dc.subjectagent paradigmeng
dc.subjectintelligent prefetching over wireless mediaeng
dc.subject.ddc330 Wirtschaft
dc.titleA generic architecture for hybrid intelligent systems
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10060836
dc.identifier.doihttp://dx.doi.org/10.18452/3786
dc.subject.dnb17 Wirtschaft
local.edoc.container-titleSonderforschungsbereich 373: Quantification and Simulation of Economic Processes
local.edoc.container-issn1436-1086
local.edoc.pages6
local.z-edoc.journal-periodikumAusgabe113,
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1998
local.edoc.container-issue113
local.edoc.container-year1998
local.edoc.container-erstkatid2135319-0

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