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Weitersagen:


Herausgeber: 
  • Anna V. Kononova
  • Niki van Stein
  • Explainable AI for Evolutionary Computation 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Mai 2026  
    Genre:  EDV / Informatik 
     
    AutomatedAlgorithmConfiguration / Benchmarking / evolutionarycomputation / ExplainableArtificialIntelligence / ExplainableDecisionMaking / ExploratoryLandscapeAnalysis / metaheuristics / sensitivityanalysis
    ISBN:  9789819625420 
    EAN-Code: 
    9789819625420 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 11 mm 
    Gewicht:  355 gr 
    Seiten:  204 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book explores the intersection between explainable artificial intelligence (XAI) and evolutionary computation (EC). In recent years, the fields of XAI and EC have emerged as vital areas of study within the broader domain of artificial intelligence and computational intelligence. XAI seeks to address the pressing demand for transparency and interpretability in AI systems, enabling their decision-making processes to be scrutinised and trusted. Meanwhile, EC offers robust solutions to complex optimisation problems across diverse and challenging domains, drawing upon the principles of natural evolution. While each field has made significant contributions independently, their intersection remains an underexplored area rich with transformative potential. This book charts a path towards advancing computational systems that are transparent, reliable, and ethically sound. It aims to bridge the gap between XAI and EC by presenting a comprehensive exploration of methodologies, applications and case studies that highlight the synergies between these fields. This book will serve as both a resource and an inspiration, encouraging researchers and practitioners within XAI and EC, as well as those from adjacent disciplines, to collaborate and drive the development of intelligent computational systems that are not only powerful but also inherently trustworthy.

      



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