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dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorde Paz Santana, Yanira
dc.contributor.authorBajo, Javier
dc.date.accessioned2017-09-06T09:05:00Z
dc.date.available2017-09-06T09:05:00Z
dc.date.issued2008
dc.identifier.citationStudies in Fuzziness and Soft Computing Soft Computing Applications in Industry. pp. 311-330.
dc.identifier.isbn978-3-540-77464-8 (Print) / 978-3-540-77465-5 (Online)
dc.identifier.issn1434-9922 (Print) / 1860-0808 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/134496
dc.description.abstractThis paper presents a case-based reasoning system developed to generate an efficient and proactive ambient intelligent application. Ambient Intelligence (AmI) proposes a new way to interact between people and technology, where this last one is adapted to individuals and their context (Friedewald and Da Costa 2003). The objective of Ambient Intelligence is to develop intelligent and intuitive systems and interfaces capable to recognize and respond to the user’s necessities in a ubiquitous way, providing capabilities for ubiquitous computation and communication, considering people in the centre of the development, and creating technologically complex environments in medical, domestic, academic, etc. fields (Susperregui et al. 2004). Ambient Intelligence requires new ways for developing intelligent and intuitive systems and interfaces, capable to recognize and respond to the user’s necessities in a ubiquitous way, providing capabilities for ubiquitous computation and communication. The multi-agent systems (Wooldridge and Jennings 1995) have become increasingly relevant for developing distributed and dynamic intelligent environments. A case-based reasoning system (Aamodt and Plaza 1994) has been embedded within a deliberative agent and allows it to respond to events, to take the initiative according to its goals, to communicate with other agents, to interact with users, and to make use of past experiences to find the best plans to achieve goals. The deliberative agent works with the concepts of Belief, Desire, Intention (BDI) (Bratman 1987), and has learning and adaptation capabilities, which facilitates its work in dynamic environment.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.subjectComputer Science
dc.titleA CBR System: The Core of an Ambient Intelligence Health Care Application
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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