Complexity: A Guided Tour
What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields.
Stats for nerds
6recommend
8mentions
8people
2010–2025years
75% recommend25% neutral
Mentions per year
What Hacker News says
- You're right to flag the distinction between symbols and substance, but I think you're misapplying it here.
I'm not conflating symbolic systems with the physical substrate: they're obviously different levels of abstraction. What I am saying is that symbolic reasoning, language, creativity, and knowledge all emerge from the same underlying physical processes. They're not magic. They're not floating in some Platonic realm. They’re instantiated in real, measurable patterns, whether in neurons or silicon.
You can't have metaphysics without physics. And we have solid evidence, from neuroscience, from pharmacology, from evolutionary biology, that the brain's symbolic output is fundamentally a physical phenomenon. Injuries, chemicals, electrical stimulation, they all modulate “metaphysical” experience in completely physical ways.
Emergence matters here. Yes, atoms aren’t thoughts, but enough atoms arranged the right way do start behaving like a thinking system. That’s the whole point of complex systems theory, chaos theory, and even early AI work like Hofstadter and Dennett. I recommend "Gödel, Escher, Bach", or Melanie Mitchell's "Complexity: A Guided Tour", if you're curious.
If you're arguing there's something else, some kind of unphysical or non-emergent component to knowledge or creativity, I'd honestly love to hear more, because that's a bold claim. But waving away the physical substrate as irrelevant doesn’t hold up under scrutiny.
- The scientific method wasn’t novel to the western world. It’s origins date back to when the Moors conquered the southern half of western europe - and by almost all historian accounts - modernized many institutions over the subsequent hundreds of years (eg, from cutlery to math and science).
I think the most relevant book on the west’s success is called complexity: a guided tour
- The Pattern on the Stone by Danny Hillis (https://en.m.wikipedia.org/wiki/The_Pattern_on_the_Stone)
Complexity a Guided Tour by Melanie Mitchell (https://melaniemitchell.me/BooksContent/CAGTReviews.html)
- Nonlinear Dynamics and Chaos by Steven Strogatz is pretty good. Nonlinear dynamics is one of the backbones of complex systems, so it's worth delving into. Graph theory/topology is a close second. Complex Networks by Latora, Nicosia, and Russo is a nice introduction to the graph-theoretical perspective. Complexity: A Guided Tour by Melanie Mitchell is a nice and brief introduction. I can also recommend Spin Glasses and Complexity by Stein and Newman. Spin glasses are basically the "model organism" of complexity science, so it wouldn't hurt to get acquainted with them.
- Melanie Mitchell’s “Complexity: A Guided Tour” is a superb introduction to this area.
And while I’m plugging her books, her latest one is one of the best-written lay-audience books about machine learning and AI that I’ve seen. I strongly recommended it for anybody curious about the field, and also for people working in the area- her explanations are crystal-clear but not dumbed down in the slightest. It’s called “Artificial Intelligence: A Guide for the Thinking Person.”
- Along with Meadows' Thinking in Systems I read Mitchell's Complexity: A Guided Tour, which is just that - a reasonably superficial tour over many examples. It's a very good starting point since it's got a long bibliography.
