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    1. Data och IT
    2. Databaser

    Computational Intelligence in Generative Artificial Intelligence

    Uncertainty Treatment and Decision-Making

    AvPedro Yobanis Piñero Pérez,Iliana Pérez Pupo

    Inbunden, Engelska, 2026

    Del i serien Studies in Computational Intelligence

    3 079 kr

    Kommande

    Beskrivning

    This book is aimed at all those interested in the combined application of computational intelligence techniques and Generative Artificial Intelligence for Uncertainty Treatment and Decision Making.The book is organized into three parts. The first part groups work related to new algorithms and techniques for handling uncertainty in generative artificial intelligence models. It also addresses topics associated with regulatory models for the development of Artificial Intelligence. The second part is dedicated to articles related to architectures of agentic artificial intelligence solutions. The third part includes works dedicated to supporting decision-making under uncertainty in business and engineering environments.This book combines different artificial intelligence techniques for solving decision-making problems, among which the following stand out: generative artificial intelligence, linguistic data summarization techniques, neutrosphophic theory, word computing, among other techniques. The techniques proposed in the book aim to simulate human tolerance in decision-making processes in environments with uncertainty and imprecision.The authors of the book stand out for their extensive experience in the development of basic and applied applications of computational intelligence. The authors Pedro Y. Piñero Pérez, Iliana Pérez Pupo, Janusz Kacprzyk and Rafael E. Bello Pérez have published several books associated with artificial intelligence and applied computational intelligence. They continue to work on fundamental and applied research on different artificial intelligence techniques to assist decision-making in different areas of knowledge.

    Produktinformation

    • Utgivningsdatum:2026-10-18
    • Mått:155 x 235 x undefined mm
    • Format:Inbunden
    • Språk:Engelska
    • Serie:Studies in Computational Intelligence
    • Antal sidor:375
    • Förlag:Springer Nature Switzerland AG
    • ISBN:9783032292872

    Utforska kategorier

    • Databaser inom Data och IT
    • Artificiell intelligens inom Data och IT

    Mer om författaren

    Janusz Kacprzyk born July 12, 1947, is a distinguished Polish engineer and mathematician, internationally recognized for his pioneering contributions to computational and artificial intelligence, specifically in fields such as fuzzy and intuitionistic sets, mathematical optimization, and decision-making under uncertainty. He currently serves as a professor of Computer Science at the Systems Research Institute of the Polish Academy of Sciences and at the Warsaw School of Applied Information Technology and Management (WIT). With an outstanding editorial career, he is the editor-in-chief of various scientific journals and several prestigious Springer book series, including Studies in Fuzziness and Soft Computing, Studies in Computational Intelligence, Advances in Intelligent and Soft Computing, and the Intelligent Systems Reference Library. Additionally, he serves on the editorial boards of approximately 40 scientific journals and is a member of international advisory boards for publications such as Fuzzy Sets and Systems and the International Journal of Intelligent Systems.Pedro Y. Piñero Pérez, is a doctor in Technical Sciences, specializing in Artificial Intelligence, Cuba 2005. In 2007, he graduated as a “database specialist for e-government” at the Okinawa International Center. He has participated in different international projects associated with the development of information systems. Coordinator of the Master’s Degree in Project Management 2007-2022. Currently, he is the chief Executive executive officer (CEO) of the IADES commercial company and co-coordinator of the IADES Community, both institutions dedicated to the development of new Artificial Intelligence technologies for Sustainable Development. He holds several intellectual property registrations associated with systems for business decision-making and multiple publications in journals and books.Iliana Pérez Pupo, is a  doctor in Technical Sciences from the National Board of Automatics and Computing (Artificial Intelligence), Cuba 2021. In 2011, she graduated from the Postgraduate Program of Excellence Master's Degree in Project Management at the University of Informatics Sciences. In her professional career, she has participated in different international projects associated with SCADA systems for the Oil Industry and Decision-Making in Project Management. Currently, she is the chief operating officer (COO) of the IADES commercial company and co-coordinator of the IADES Community, both entities dedicated to the development of new Artificial Intelligence technologies for Sustainable Development. She develops oriented fundamental research and applied research on different artificial intelligence techniques to support decision-making in various areas of knowledge. She holds several intellectual property registrations for intelligent systems for integrated project management.Rafael Bello Perez received his Bachelor degree in Mathematics and Computer Science (1982) at Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara, Cuba, and his Ph.D. in Mathematics at UCLV in 1988. He is a full Professor at Computer Science Department, UCLV, Cuba, and exhibits a long record of academic exchange with many universities in Latin America, Europe, and Asia. He has been a visiting scholar at some universities in Spain, Germany, and Belgium. He has taught more than 200 undergraduate and graduate courses in those academic centers. His current position is the director of the Research Center on Informatics at UCLV. He is the chief of the Scientific Council of UCLV. He has the especial academic category of ¨Profesor de Merito¨ of UCLV, and he is a visiting professor in other Cuban universities.

    Innehållsförteckning

    • .- Modeling and Handling Uncertainty in Generative Artificial Intelligence..- Combining OWA Neutrosophic Operators and LogProbs for Uncertainty Evaluation in Agentic AI Outputs..- Evaluation of Plausibility and Robustness in Counterfactual Explanations..- Regulatory Model and Best Practices for the Development of Artificial Intelligence in Contexts of Uncertainty..- Uncertainty: another aspect to consider in XAI..- Architectures and Solutions Based on Intelligent Agents..- Multilayer Memory Architecture for Multi-agent Intelligent Decision-Making in uncertainty environment..- Layered hybrid architecture for uncertainty mitigation in virtual assistants..- Prototype of an Autonomous System for Integrated Cybersecurity Management..- Algorithms and Patterns for Building Agent-Based Artificial Intelligence Solutions assisted by Soft Computing Techniques..- Artificial Intelligence for Advanced Data Analysis and Decision-Making under Uncertainty..- Ecosystem for Decision-Making in High-Performance Athletes Combining Generative AI and Soft Computing Under Uncertainty..- Generative AI Enhanced Predictive Prescriptive Analytics for Uncertainty Aware Decision Making: Talent Management Case Study..- Probabilistic Tree-Based Approach for Linguistic Data Summarization and Knowledge Generation under Uncertainty in Sustainability Analysis..- Computational Intelligence and Generative Artificial Intelligence for Legal Claims Management Under Uncertainty.