Entelligence: Evolutionary Intelligence

Why start this blog? I am aiming to documenting the progress on the idea of simulating biological evolution to achieve intelligent machines or behaviors While working in molecular biology, bioinformatics, and artificial intelligence, it seems this evolutionary path to intelligent machines is becoming increasingly feasible.

I quote Turing's statement below about evolutionary intelligence from here

In his 1948 paper, Turing identified three broad approaches by which human-competitive machine intelligence might be achieved.

The first approach was a logic-driven search. Turing’s interest in this approach is not surprising in light of Turing’s own pioneering work in the 1930s on the logical foundations of computing.

The second approach for achieving machine intelligence was what he called a “cultural search” in which previously acquired knowledge is accumulated, stored in libraries, and brought to bear in solving a problem¾the approach taken by modern knowledge-based expert systems.

Turing’s first two approaches have been pursued over the past 50 years by the vast majority of researchers using the methodologies that are today primarily associated with the term “artificial intelligence.”

However, Turing also identified a third approach to machine intelligence in his 1948 paper entitled “Intelligent Machinery” (Turing 1948, page 12; Ince 1992, page 127; Meltzer and Michie 1969, page 23), saying:

“There is the genetical or evolutionary search by which a combination of genes is looked for, the criterion being the survival value.” (Emphasis added).

Turing did not specify in 1948 how to conduct the “genetical or evolutionary search” for solutions to problems. In particular, did not mention the concept of a population or recombination. However, he did point out in his 1950 paper “Computing Machinery and Intelligence” (Turing 1950, page 456; Ince 1992, page 156):

“We cannot expect to find a good child-machine at the first attempt. One must experiment with teaching one such machine and see how well it learns. One can then try another and see if it is better or worse. There is an obvious connection between this process and evolution, by the identifications

“Structure of the child machine = Hereditary material

“Changes of the child machine = Mutations

“Natural selection = Judgment of the experimenter”

Thus, Turing correctly perceived in 1948 and 1950 that machine intelligence might be achieved by an evolutionary process in which a description of a computer program (the hereditary material) undergoes progressive modification (mutation) under the guidance of natural selection (i.e., selective pressure in the form of what is now usually called “fitness” by practitioners of genetic and evolutionary computation).