October 2023
Intermediate to advanced
296 pages
4h 26m
Japanese
Overview
人工生命の研究分野で開発された、「発散型」アルゴリズムが近年注目を浴びています。深層学習を含む多くの機械学習アルゴリズムが、1つの最適解を求める「収束型」のアルゴリズムであるのに対し、進化計算をベースにして開発された「発散型」アルゴリズムは多様な解を求めることができる画期的なアプローチです。本書はこの革新的な発散型アルゴリズムに焦点を当て、進化計算の基礎となる集団的探索の考え方、既存の収束型アルゴリズムとの違い、そして有用性について説明します。NEAT、新規性探索、品質多様性、共進化といった代表的なアルゴリズムのほか、CPPN、POETなどの最新アルゴリズムも取り上げています。この本は、未来のAI技術を先導するための必読書です。
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