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dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorLi, Weigang
dc.contributor.authorBajo Pérez, Javier
dc.contributor.authorWu, Fei
dc.contributor.authorLi, Tiancheng
dc.date.accessioned2017-09-05T10:59:03Z
dc.date.available2017-09-05T10:59:03Z
dc.date.issued2016
dc.identifier.citationFrontiers of Information Technology & Electronic Engineering. Volumen 17 (4), pp. 281-282.
dc.identifier.issn2095-9184 (Print) 2095-9230 (Online)
dc.identifier.urihttp://link.springer.com/article/10.1631/FITEE.DCAI2015#Abs1
dc.identifier.urihttp://hdl.handle.net/10366/134259
dc.description.abstract4:1! Google’s artificial intelligence (AI) program, AlphaGo, has won Go Master Lee Sedol in a best-of-five competition held in Korean March 9−15, 2016. Seen by many as a landmark moment for AI, the outcome did not come as a surprise, considering the excellent combination of 1920 CPUs with sophisticated AI algorithms, including neural networks and Monte Carlo tree search (Gibney, 2016; Silver et al., 2016). Indeed, research on distributed computing and artificial intelligence (DCAI) has matured during the last decade and many effective applications are now deployed, performing an increasingly important role in modern computer science, including the two most hyped technologies: Internet of Things and Big Data. Indeed, it is fair to say that the application of artificial intelligence in distributed environments is becoming an essential element of high added value and economic potential.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleSpecial issue on distributed computing and artificial intelligence
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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