June 2002

Outline of my approach for researching

mechanisms for learning and adaptation by means of evolution of brain structures

Menno Rubingh
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I'm fascinated by artificial intelligence, memetics, evolution, and by the philosophical questions related to human intelligence. I believe that human intelligence, human consciousness, and all processes in the human brain, can be explained fully mechanically. Creating artificial intelligence which shows aspects of human-like intelligence I believe to be the only way to prove that the human mind is 100% mechanical.

My model of human brain operation and human learning is that inside the brain, items of knowledge undergo an evolutionary process of selection, mutation, and elimination. Human inventiveness results from random mutations in existing items of knowledge, and weeding out mistfit mutations.

Moreover, the human brain exists not in isolation, but is in constant interaction with the body and the environment outside of the brain: it receives sensor input and sends out motor control output signals. That is, the brain as a whole functionally plays same role as that of a single McCulloch-and-Pitts like neuron, receiving sensor inputs on its input terminals and sending out a motor signal. It is possible to successfully control a simple autonomous robot with a brain consisting of a very small number (about 2 to 10) of such neuron cells. Brains of more ``intelligent'' entities would be constructed from more complex combinations of neuron cells.


What I aim to do is to extend the above picture of an artificial brain constructed from neuron cells with the following:


A terse outline of the current state of my work is given in (a message I posted on the pcp-discuss mailing list of the PCP project (see
Detailed information on a specific part of the actual software that I've created as a part of this work can be found in, particularly in

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