Complexity Space in Intelligent Systems: A Network Theory Approach

This book offers a new way of understanding intelligence across biological minds, artificial systems, and emerging human–machine hybrids. It introduces complexity space: a conceptual framework in which very different intelligences can be described, compared, and related on common ground.

Rather than focusing on hardware or algorithms, the book treats intelligences as networks of relationships. A central idea is a simple structural method — the absolute difference matrix — which makes it possible to recognise deep similarities between systems that look completely different on the surface, from genetics and brains to artificial and hybrid intelligences.

Across twenty chapters, the book develops an extension of entropy, explores emergence and coincidence, and shows how learning and creativity can be understood as movement through structured spaces.

Written without heavy mathematics, it is aimed at any thoughtful reader interested in how AI reshapes what intelligence itself means.