03806nam 22005895 450 991059005370332120230810231711.09789811940590(electronic bk.)978981194058310.1007/978-981-19-4059-0(MiAaPQ)EBC7078235(Au-PeEL)EBL7078235(CKB)24750398700041(DE-He213)978-981-19-4059-0(PPN)264192443(EXLCZ)992475039870004120220828d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierChoice Computing: Machine Learning and Systemic Economics for Choosing /by Parag Kulkarni1st ed. 2022.Singapore :Springer Nature Singapore :Imprint: Springer,2022.1 online resource (254 pages)Intelligent Systems Reference Library,1868-4408 ;225Includes index.Print version: Kulkarni, Parag Choice Computing: Machine Learning and Systemic Economics for Choosing Singapore : Springer,c2022 9789811940583 Introduction -- 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.This 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.Intelligent Systems Reference Library,1868-4408 ;225Computational intelligenceMachine learningComputer scienceMathematicsComputational IntelligenceMachine LearningMathematics of ComputingComputational intelligence.Machine learning.Computer scienceMathematics.Computational Intelligence.Machine Learning.Mathematics of Computing.006.31Kulkarni Parag845705MiAaPQMiAaPQMiAaPQ9910590053703321Choice Computing: Machine Learning and Systemic Economics for Choosing3567776UNINA