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Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions

Many firms provide their customers with online information products which require limited resources such as server capacity. This book develops allocation mechanisms that aim to ensure an efficient resource allocation in modern IT-services. Recent methods of artificial intelligence, such as neural n...

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Detalles Bibliográficos
Autores principales: Schwind, Michael, Künzi, H P, Fandel, G
Lenguaje:eng
Publicado: Springer 2007
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-540-68003-1
http://cds.cern.ch/record/2116496
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author Schwind, Michael
Künzi, H P
Fandel, G
author_facet Schwind, Michael
Künzi, H P
Fandel, G
author_sort Schwind, Michael
collection CERN
description Many firms provide their customers with online information products which require limited resources such as server capacity. This book develops allocation mechanisms that aim to ensure an efficient resource allocation in modern IT-services. Recent methods of artificial intelligence, such as neural networks and reinforcement learning, and nature-oriented optimization methods, such as genetic algorithms and simulated annealing, are advanced and applied to allocation processes in distributed IT-infrastructures, e.g. grid systems. The author presents two methods, both of which using the users??? w
id cern-2116496
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2007
publisher Springer
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spelling cern-21164962021-04-21T19:56:42Zdoi:10.1007/978-3-540-68003-1http://cds.cern.ch/record/2116496engSchwind, MichaelKünzi, H PFandel, GDynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctionsMathematical Physics and MathematicsMany firms provide their customers with online information products which require limited resources such as server capacity. This book develops allocation mechanisms that aim to ensure an efficient resource allocation in modern IT-services. Recent methods of artificial intelligence, such as neural networks and reinforcement learning, and nature-oriented optimization methods, such as genetic algorithms and simulated annealing, are advanced and applied to allocation processes in distributed IT-infrastructures, e.g. grid systems. The author presents two methods, both of which using the users??? wSpringeroai:cds.cern.ch:21164962007
spellingShingle Mathematical Physics and Mathematics
Schwind, Michael
Künzi, H P
Fandel, G
Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title_full Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title_fullStr Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title_full_unstemmed Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title_short Dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
title_sort dynamic pricing and automated resource allocation for complex information services: reinforcement learning and combinatorial auctions
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-540-68003-1
http://cds.cern.ch/record/2116496
work_keys_str_mv AT schwindmichael dynamicpricingandautomatedresourceallocationforcomplexinformationservicesreinforcementlearningandcombinatorialauctions
AT kunzihp dynamicpricingandautomatedresourceallocationforcomplexinformationservicesreinforcementlearningandcombinatorialauctions
AT fandelg dynamicpricingandautomatedresourceallocationforcomplexinformationservicesreinforcementlearningandcombinatorialauctions