Bio-Inspired Artificial Intelligence: How Self and Complexity Emerge in Biological Systems

Although the connections between biological systems and computing have been many in many other places, I found this primer, Bio-Inspired Artificial Intelligence, especially interesting for its chapter on immunological systems. The contention that the basis of identity (self vs. other) and even intelligence has its evolutionary basis in the adaptive evolution on immune systems is just too fascinating to ignore. The authors spend considerable time working through basics of immunological response and conceptualizing what they term shapespace. I think this is great text to selectively tip into for this topic alone - since so much of the literature for computational biology is focused on bioinformatics (strong matching), genomics, proteomics, and them a fast shift to systems biology.

I actually think the relatively primitive immunological system (pattern matching engine) is a superb place to ask some fundamental questions on what we think of as the self and how it evolves in a dynamic, evolutionary ecosystem constantly deluged by bacteria, prions, viruses, electro-nmagnetic radiation, DNA replication errors (cancers), and even more elaborated bio-programming systems (namely: memes). I like the approach, since it posits a very small number of non-supernatural and metaphysical entities to account for both the emergence of intelligence, collective coordination, cooperation, and the explosion of biodiversity.

As one person put it: Natural evolution is a good analogy to this method–the rules of evolution (selection, recombination/reproduction, mutation and more recently transposition) are in principle simple rules, yet over thousands of years have produced remarkably complex organisms.