The Evolution of Modularity in Networks

There is a "near-universal presence of modularity in biological networks as diverse as neural networks -- such as animal brains -- and vascular networks, gene regulatory networks, protein-protein interaction networks, metabolic networks and even human-constructed networks such as the Internet."

It turns out that by adding a cost to adding more links, simulations of evolution soon evolve modularity.

In my chapter Getting to the Hayekian Network, I suggest different purposes for different network architectures. The modularity argument contributes to this, suggesting that any time you have a complex network, you will find radical decentralization through the creation of modules.

Further, this suggests that the evolutionary psychologists are on to something in positing the brain to be constructed of modules. One still needs to address, though, the presence of "general intelligence" in humans. How those modules are connected and communicate matters. 

Fractal Fitness

The complexity of fractal geometry of a bird's plumage indicates its level of fitness. Does this imply that the complexity of fractal geometry of an artist's art indicates the artist's (or art work's) level of fitness? How about the novelist or poet? My might these be indications of fitness? Complex patterns are more difficult to produce than either complicated or simple patterns. If you have what it takes to make complex patterns, you are probably fit in other areas as well.

Neurons As Agents Interacting in a Spontaneous Order Network

Daniel Dennett has come to realize that the brain works in pretty much the same way as Hayek argued spontaneous orders work -- including the brain. The conflicts which arise among the neurons and the genes are precisely the kind I learned from J.T. Fraser underlie all complex processes.

Indeed, it turns out that if you understand how humans as agents interact in complex, self-organizing networks, you have a pretty good idea of how neurons interact in the brain. Hayek would not be surprised. Neither am I.