LEADER 03806nam 22005895 450 001 9910590053703321 005 20230810231711.0 010 $a9789811940590$b(electronic bk.) 010 $z9789811940583 024 7 $a10.1007/978-981-19-4059-0 035 $a(MiAaPQ)EBC7078235 035 $a(Au-PeEL)EBL7078235 035 $a(CKB)24750398700041 035 $a(DE-He213)978-981-19-4059-0 035 $a(PPN)264192443 035 $a(EXLCZ)9924750398700041 100 $a20220828d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aChoice Computing: Machine Learning and Systemic Economics for Choosing /$fby Parag Kulkarni 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (254 pages) 225 1 $aIntelligent Systems Reference Library,$x1868-4408 ;$v225 300 $aIncludes index. 311 08$aPrint version: Kulkarni, Parag Choice Computing: Machine Learning and Systemic Economics for Choosing Singapore : Springer,c2022 9789811940583 327 $aIntroduction -- Decoding Choosing -- ML of Choosing: Architecting Intelligent Choice Framework -- Machine Learning of Choice Economics -- Co-operative Choosing: Machines and Humans Thinking Together to Choose the Right Way -- Choice Architecture ? Machine Learning Framework -- Artificial Consciousness and Choosing (Towards Conscious Choice Machines) -- Choice Computing and Creativity -- Experimental Choice Computing and Choice Learning Through Real-Life Stories -- Beyond Choice Computing. 330 $aThis book presents thoughts and pathways to build revolutionary machine learning models with the new paradigm of machine learning to adapt behaviorism. It focuses on two aspects ? one focuses on architecting a choice process to lead users on the certain choice path while the second focuses on developing machine learning models based on choice paradigm. This book is divided in three parts where part one deals with human choice and choice architecting models with stories of choice architects. Second part closely studies human choosing models and deliberates on developing machine learning models based on the human choice paradigm. Third part takes you further to look at machine learning based choice architecture. The proposed pioneering choice-based paradigm for machine learning presented in the book will help readers to develop products ? help readers to solve problems in a more humanish way and to negotiate with uncertainty in a more graceful but in an objective way. It will help to create unprecedented value for business and society. Further, it will unveil a new paradigm for modern intelligent businesses to embark on the new journey; the journey of transition from shackled feature rich and choice poor systems to feature flexible and choice rich natural behaviors. 410 0$aIntelligent Systems Reference Library,$x1868-4408 ;$v225 606 $aComputational intelligence 606 $aMachine learning 606 $aComputer science$xMathematics 606 $aComputational Intelligence 606 $aMachine Learning 606 $aMathematics of Computing 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aComputer science$xMathematics. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 615 24$aMathematics of Computing. 676 $a006.31 700 $aKulkarni$b Parag$0845705 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910590053703321 996 $aChoice Computing: Machine Learning and Systemic Economics for Choosing$93567776 997 $aUNINA