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essays and commentary
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Regarding the residence of the programs of the mind, and with the aim of minimizing the required complexity of the computing-element program, assume that the computing-element program provides various learning algorithms—such as learning by trial and error, learning by analogy, and learning by copying—which, in effect, allow intelligent particles to program themselves. Specifically, with this assumption, each program of the mind—such as the program to recognize a face—exists as part of the state information of those bions occupying that part of the brain that is the site for that program’s operation.
For reasons of efficiency, assume that the overall learning mechanism provided by the computing-element program includes a very high-level language in which learned programs are written. Then, to run a learned program, the computing-element program interprets each high-level statement of that learned program by executing the computing-element program’s own corresponding low-level functions.
Regarding the type of learning used by the brain bions to construct the various programs of the mind, at least some of the learning is copying from other minds., Once a specific learned program is established and in use by one or more bions, other bions can potentially copy that program from those bions that already have it, and then over time potentially evolve that learned program by using any of the learning methods.,
Regarding learned programs within moving particles, absolute motion thru space is the norm for particles. And as an intelligent particle moves thru space, each successive computing element that receives that intelligent particle continues running that intelligent particle’s learned programs, if any, from the point left off by the previous computing element.
 Given the discussion of rebirth in section 6.3, at least some of the various programs of the mind are simply retained from the previous life, and reused.
 Given the common observation that children typically resemble their parents, and given the more specific observation made by Arthur Schopenhauer in the 19th century—that general intelligence seems to be inherited from the mother, and personality from the father—it follows that in the typical case, there is at least some copying from the minds of both parents, before and/or after birth. More specifically, for a typical person, copied from each parent is a partial allocation plan (section 9.6) that determines to a large extent intelligence (the partial allocation plan copied from the mother) and personality (the partial allocation plan copied from the father).
Schopenhauer made another interesting observation, regarding the basis of sexual attraction: Each person has within himself an inborn mental model of what an ideal person should look like. And the extent to which that person deviates from that internal model, that is the extent to which that person will find correcting or offsetting qualities attractive in the opposite sex.
 In effect, learned programs undergo evolution by natural selection: the environment of a learned program is, at one end, the input datasets that the learned program processes; and, at the other end, the positive or negative feedback from whatever uses the output of that learned program, being either one or more learned programs in the same or other bions, and/or the soliton described in chapter 6.
It is this environment, in effect, that determines the rate of evolutionary change in the learned program. The changes themselves are made by the aforementioned learning algorithms in the computing-element program. Presumably these learning algorithms use the feedback from the users of the output of that learned program, to both control the rate of change, and to guide both the type and location of the changes made to that learned program. Within these learning algorithms, negative feedback from a soliton (described in chapter 6) probably carries the most weight in causing these algorithms to make changes.
Note that evolutionary change can include simply replacing the currently used version of a learned program, by copying a different version of that learned program, if it is available, from those bions that already have it. The sharing of learned programs among bions appears to be the rule—and, in effect, cooperative evolution of a learned program is likely.
 An example of a learned program that is widely shared is the learned program (or programs) for vision.
Although one may imagine that vision is a simple process of merely seeing the image that falls on the eye, that is not the case at all (note that the fact that we all see things alike, because we are all using the same program, adds to this illusion of simplicity). Instead, the process of human vision—converting what falls on our eyes into what we consciously see in our minds—is very complex, with many rules and algorithms (Hoffman, Donald. Visual Intelligence. W. W. Norton, New York, 1998):
Perhaps the most surprising insight that has emerged from vision research is this: Vision is not merely a matter of passive perception, it is an intelligent process of active construction. What you see is, invariably, what your visual intelligence constructs. [Ibid., p. xii]
The fundamental problem of vision: The image at the eye has countless possible interpretations. [Ibid., p. 13]
The fundamental problem of seeing depth: The image at the eye has two dimensions; therefore it has countless interpretations in three dimensions. [Ibid., p. 23]
About our senses, it isn’t just what we see that is a construction of our minds. Instead, as Hoffman says:
I don’t want to claim only that you construct what you see. I want to claim that, at a minimum, you also construct all that you hear, smell, taste, and feel. In short, I want to claim that all your sensations and perceptions are your constructions.
And the biggest impediment to buying that claim comes, I think, from touch. Most of us believe that touch gives us direct contact with unconstructed reality. [Ibid., p. 176]
To prove this idea that our sense perceptions are mental constructions, one only needs to point at experiments that show the percipient experiencing some sense perception that has no basis in physical reality. For vision, there are many different optical illusions that cause one to see something that is not in the physical image. For touch, Hoffman cites experimental results regarding an effect that was “discovered by accident in the early 1970s by Frank Geldard and Carl Sherrick” (Ibid., p. 180). These experiments consist of making during a short time interval a small number of taps at different points on a test subject’s forearm. Depending on the location and timing of the different taps, the subject will feel one or more interpolated taps at locations where no physical taps were made. For example, Hoffman describes an experiment that delivers two quick physical taps at one point, quickly followed by one physical tap at a second point, and the subject reports feeling the three taps but with the second tap lying between those two points instead of being at the first point where the actual second physical tap was made (Ibid., p. 181). As Hoffman notes, this means that the entire perception of the three taps was constructed by the mind after the three taps had happened, because the interpolated tap point is dependent on knowing both the first and second points (the two end-points for the interpolation), and this second point is only known when the third and final physical tap happens.
 It is reasonable to assume that each intelligent particle has a small mass—i.e., its mass attribute has a positive value—making an intelligent particle subject to both gravity and inertia. This assumption is consistent with how the intelligent particles currently associated with the Earth, including cell-occupying bions, stay with the Earth as it moves many kilometers per second thru space due to a combination of gravitational and inertial effects including the rotation of the Earth, the Earth’s rotation around the Sun, and the rotation of the solar system around the galactic core.