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Springer Explainable AI for Evolutionary Computation Book

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Description

Explore the connection between explainable artificial intelligence (XAI) and evolutionary computation (EC) in this Springer publication. As AI systems become more common, the demand for transparency and interpretability grows. This book addresses the need to make decision-making processes scrutinizable and trustworthy through XAI. At the same time, the text covers how evolutionary computation provides solutions for complex optimization problems in various challenging domains by using principles of natural computing. This work is a vital resource for those studying the intersection of these two emerging areas within the broader field of computational intelligence.

Key Features

This Springer book examines the intersection of explainable artificial intelligence and evolutionary computation.

Learn how XAI addresses the need for transparency and interpretability in AI decision-making processes.

Discover how evolutionary computation provides solutions for complex optimization problems across diverse domains.

Part of the Natural Computing Series, this text focuses on vital areas of study within computational intelligence.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
03 May 2025
Listed Since
07 December 2024

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