Beepers are simple little creatures that live in a very small computer. They are real in the sense that they interact with the world, each other, and themselves. Their behavior is an ongoing process of development, built out of these interactions.

The beepers have been designed with functional characteristics that parallel some of the principles of mammalian neurological interaction. They are a product of a limited sampling of a diverse range of scientific literature, as well as of a number of assumptions; and of corrections brought about by problems exposed in development of the program.

Program Description

The program defines two beepers. The program organizes the computer into two sets of Ns (neurons). It handles each N , one at a time. It looks at each N to see if it is active, or at rest. It does this with one beeper, and then it essentially repeats itself to do it with the other beeper. Then the whole cycle is repeated.

In each cycle, a different pattern of Ns is involved. It is this pattern, and its changing character relative to itself, that is the developing definition of self-meaning. At the same time, it is a depiction of the world, pieced together with an ongoing influx of abstractions from the world.

You could say that the main job of the program is to detect the quiet Ns as quickly as possible. I guess that in any given cycle, or "reality frame," there should be approximately 10% of the Ns active. Thus, the program has been set up to run through the quiet majority of Ns as quickly as possible. It will become apparent that, in terms of what we’re attempting to accomplish here, the limiting factor imposed by the hardware is not memory capacity, but rather, speed. To get more Ns involved you need more speed. Memory comes more from the number of Ns than from how big each one is; though both factors contribute. You have about 10¹⁰ or 10¹¹ Ns; each one "knows" up to 10⁴ other Ns. The number of Ns is 10⁶ times more important than their "size" — their capacity to immediately access the rest of the potential process — for humans.

To facilitate speed, and for a few other conveniences, the Ns themselves are split up into two parts. The small part occupies two bytes, and the "large" part takes sixteen. So, each N consists of 18 8-bit bytes of data. Of course, the data won’t run itself; the bulk of each N is actually the section of the program called the "N Loop." This is like the DNA; it tells each N how to behave, and they all behave about the same way. It’s mainly their relative "position" and data that differentiate them. Obviously, this is simplistic; but given the starting restraints, the approach is the best compromise I could develop.

The first byte of N, in its small part, is its dendrite area. Other Ns will stimulate this area (literally!) by increasing the numeric hex value there. (In a prior, more complex system, the N was sensitive to the particular pattern of bits set in this dendrite register... it kept a short list of "familiar" stimulation patterns.) This system is FM, like real Ns are; and a given N will "Fire" with a higher rate of repetition if its dendrite area is being more heavily stimulated (the maximum rate is once every other Main Loop cycle — one loop for each beeper).

For purposes of speed of indexing data, the small part needed a second byte; as a sort of "spacer." Since these first two bytes are visible on the screen (in slow mode only) for one of the two beepers, the best other use to display was a byte called "delay." This byte is similar to the dendrite IN# byte, in that it relates to the activity level of the given N it belongs to. It is needed to determine how often the N will fire. It’s a timer that runs out to trigger firing that N on that main cycle. It provides an opportunity, as does the IN#, to custom tailor the response and activity characteristics of a given N in a given "cortical area."

The memory map of the C128 from 2000 toward 35FF, is taken up by this first small part of some twenty-eight hundred Ns (all addresses are in hex; all quantities are decimal, unless preceded by a "$"). In bank 00 there is one set for one beeper, and in bank 01 there is the other set for the other beeper. The program occupies 0B00 to 1000, and 1300 to 1FFF, almost identically in each of the two banks. The rest of the area below 1300 is taken by C128 operations. The C128 also uses a few bytes starting at FF00; and the rest used by the beepers is from 3600 to FE43, and a scratch pad area above FF05. I use the Warp Drive cartridge, to speed disk loading, saves, and utilities; so there is some use up at the high end there that you have to work around.

The area from 3600 toward 4BFF is taken up by pointers. These are used by the N Loop’s indexing system to access the larger part of each N. Those larger parts take up from 4C00 toward FC00.

The first byte, in the larger set of sixteen, is called the "xth." "X" is the number of times an N can Fire before it gets tired and has to take a "time out." The time out consists of clearing the IN# — in other words, it may miss firing the next time, but then is ready to fire again, x times. This has proven to be sufficient interruption, in this system, to avoid the problem of pattern repetition; a problem especially during initial development of the data assimilation process. Pattern repetition is the tendency for a limited set of Ns to get involved with each other, and tie up all the available time, permanently. Another requirement, for dealing with this problem, is inhibition — Ns not only stimulate other Ns, but also do un-stimulation. How this has come to be implemented should be described shortly, when discussing the gross organization of N interconnection.

The remaining fifteen bytes per N contain the intelligence. They are a list of which other Ns a given N will hit when it Fires. To get on this list, you have to be a neighboring N that is active or ready to Fire at the same time that this N is going to Fire. This is the mechanism that implements the associative filing of data. The gross structure is set up in such a way that patterns, and their temporal sequence, are associated.

Each N’s list does not fill, and then just stay that way. New thoughts have a chance to work their way into the lists, at the expense of the least used data. In a very large system, the thoughts producible by that unused data would get eaten away at; but not completely. Because of the method of memory distribution, and the laws of mathematical probability that actually control reality, a faint image would almost always be retained. With this faint image, a little association through repeated need would re-install the original data — with many of the Ns involved being different ones; but with a fairly accurate re-generation of the original relative meaning.

I suspect that, in time, this process of prioritized list-filling elevates itself. Meaning is developed, relative to other meaning. Initial meaning serves as a basis out of which higher meaning can develop and interact. The initial meaning becomes less and less a focus — it is less and less used — and much of it eventually becomes essentially uninvolved.

Of the various routines in the program, the one that most defines the gross structure of "brain anatomy" is called the "Out M" routine. This routine connects sections of cortex to other sections with a general Input-to-HighArea-to-Output directed-ness. The routine is simplified and accelerated by allowing the general organization of Ns to fall where it wants to by virtue of hexidecimentality (sorry).

The C128 memory is approximately a pair of C64s — two banks of 64K of memory, accessible to an 8 bit "6502" CPU. In 6502 lingo, a page of memory is 256 8-bit bytes. For the beepers, a page of neurons is 128 neurons wide. This is because the small part is 2 bytes wide. The small part is where all the action is. The beeper dendrites are where the Fires hit. Everything else is going on in the background, or internally, within the Ns, if you will.

In addressing memory, 255 is the maximum LSB (least significant byte) for accessing a byte "on your page." To access other pages, you need an MSB (most significant byte), which can also go to 255, taking you up to 64K altogether (there are 256 addresses to each part here — ranging from 0 to 255). The "M" in "MSB" is the "M" in the "Out M" routine. The pages of Ns, 128 wide, are piled up 22 pages high. Any N can quickly affect another N directly above or below it by manipulating the MSB involved, and using the LSBs that are already in place.

What would be the "Out L" routine is broken into two routines — "Out L Stim" (collateral stim) and "AOL" (Aim the Out L list entry). These routines provide side-to-side action within a given page, while the Out M routine provides up-or-down action between the pages. Together, the system is an active matrix. The rules composing the routines have been chosen to allow the capture of temporal associations within the matrix.

When you hear the word "CAT," you hear the "C" sound first, then the "A" sound; and after this temporally-ordered combination, you hear the "T" sound. Hearing them in rapid succession conjures up whatever associations you think of when you hear the word "CAT." This works, and it works without confusing the "C" sound in cat, with the "C" sound in canary or catsup. It works right because the active word itself is a combination unlock into your mind. The important ingredients of the combination are the component sounds, and their order. The exact timing is of less consequence — but timing does produce spaces relative to other timing, and the spaces can affect the relative meaning. Relative amplitude is of even less significance. Absolute pitch is not a factor, until the physical limits of the ear are reached. Relative pitch is the primary structure of meaning in the sound train.

When you hear the word "CAT," the "C" sound produces a neural stimulation that is very similar to that which is produced by any word starting with the "C" sound. The particular pattern of Ns stimulated, leads toward the cortex, but makes several transitions along the way. At each transition there is an abundance of neural transmission leading back to the area of prior stimulation. Not only is it going the wrong way, but there is a lot of it ... about ten times as much as leading in ... and it’s usually dispersed ... scattered around randomly. How could evolution, in all its wisdom, be so careless!

All that information coming back to your ear, after the "C" sound went in, is "looking" for the next sound. It is anticipatory stimulation. It wants to mate with something familiar. If the "A" sound comes next, then a characteristic secondary pattern of feedback will be set up to look for the third sound, that is a much more unique pattern than if it were the first one fed back. Furthermore, as the real-world series of sounds pile into your ear, the feed-in, feed-back process finds its way into a geometric progression of potential combinations. Each transition area sends dispersed feedback to the one before it, as you make your way to the cortex. Generally, the feed-in pathways produce a neat orderly map of excitation at each transition area, right up to the primary cortical area of the given sense involved. (This is, of course, a simplification and generalization of what really goes on. For one thing, the neural "cycle rate" is some one thousandth of a second, so that many feedback cycles are possible within the time frame of single phonic sounds. This probably helps with handling variability of timing in phonic relationships.)

Association is at the heart of every level of the thought process. It not only controls the flow of relative meaning in your thoughts; it is the very structure of incoming communicated intelligence itself.

Extraneous neural activity, such as heart-rate stimulation, and the general random neural noise level, have no effect on consciousness, because these activities do not contribute meaning to the temporal pattern sequence. Only meaningful components can add to the resolution, depth, or degree of consciousness; because relative meaning itself is the consciousness. Would-be meaningless components can’t degrade it, because they aren’t a part of it. (I’m not referring to distracting thoughts — these you become aware of, due to their meaning.)

At the center of the stack of 22 pages of Ns, are a pair of pages called the "Out Page" and the "In Page." These can be thought of as the output and sensory ports leading from/toward the motor cortex and somatic cortex areas; or the speech motor cortex and the auditory cortex.

Sound from the true-pitch keyboard or the ear microphone is processed by the mic circuit into a voltage level that is determined by the instantaneous frequency of the sound. The voltage is converted to a resistance for the Game Port A to D. In other words, in the computer, a register has a value in it that is controlled by the pitch of the sound in the room. The sound-source should be fairly sinusoidal — it should be pure tones. Whistling is good. The keyboard and beepers each drive one of the three C128 voices, using the triangle wave form. Most other wave forms will produce unreliable error data.

Activity on the Out Page produces a pattern of dendrite IN#s on the 16 Ns in the Out Area; near the center of the Out Page; one page before the corresponding In Area on the In Page. These Out Area IN#s are used as weights on frequency centers, to arrive at a single-tone frequency result, for each given cycle with activity in the Out Area. The frequency is shifted and ranged to approximately correspond to the In Area spectrum. In other words, the Out Area is handled by the program in such a way as to simulate simplified cerebellar action. The result is used to set the frequency of a C128 voice. (In a very abstract and distilled sense, you could say the beepers have eyes for ears, and hands for a mouth.) A delay time is used to insure that tones are sounded for enough time to register accurately in the mic circuit and game port. A tone can last longer if the given Main Loop cycle is running slow that moment. The tone is delivered to the room, for pick-up by the mic as well as for monitoring beeper behavior. The temporal matrix includes exceptions and diversions that promote learning through feedback.

The Out L and Out M routines spread the In Page and Out Page activity throughout the matrix. While most pages can stim the page above or below, there is isolation between the Out Page and the In Page - except at the periphery of these pages. This leakage is meant to parallel the "voice-muscle-sense," or sense of "touch" we have in our various speaking apparatus, as well as "mind’s ear" internal data flow. The isolation between these pages defines "ends" to the system, to insure that the primary resultant communication of the system with itself is through the air; so that human interaction, through the air, will be on the same level as the system’s own basic feedback orientation.

The Out M stimulation has been channeled into one-way sections of 16 Ns of width. This simplifies handling the I/O pathways, and provides a neat set-up for bidirectional temporal loop formation.

The channel including the In Area and Out Area is granted higher status — these Out M hits are strong, to simulate reliable transmission along primary data pathways. Ns within these channels should probably be restricted from Out L hitting other Ns within the channel, on the same page; beyond this, however, any N can hit any other N on its page. The current implementation only applies this restriction in the In Area; but encourages it for all the 16 N-wide channels, on all pages, by initiating the AOL 16 Ns ahead, and placing the Out L stim (collateral stim) 16 Ns behind, the current N position on the page.

Various arrangements have been tried. Out M routines that hit +1, +3, +7 pages ahead, and -2, -4, -6 pages behind, simultaneously, for example. It didn’t much seem to matter, at least at this level of N# depth (and with an IN pattern-sensitive non-FM system), exactly how you set it up, but you must include -1 inhibition. You can have more inhibition, but you have to have -1 included. -1 inhibition means that while you hit one or more pages ahead, and/or behind, with respect to the scanning direction, you un-stimulate the N one page behind. In the system here, -1 inhibition is one page the opposite direction of the 16 N-wide channel your in. Without this rule contributing to the characteristics of propagation, the system will get tied up in tiny loops that take up all the time; while no meaningful interplay of real-world data and internal data is handled.

Pattern association, and temporal pattern sequence association, are facilitated within the overall matrix by having each active N set up pre- and post- stimulations of other Ns, that stand available for other active Ns to find simultaneously active. The stims to Ns about to be scanned this cycle, facilitate immediate pattern handling. The stims to Ns already scanned this cycle, facilitate temporal sequence handling — they are a link from one "frame" in time to the next. (In addition, any active N is a link to the future, because the stimulation level on its input is only reduced, not erased, each cycle. It is reduced a lot more when the N times out to Fire. It is cleared by the Ns Tire routine when the xth Fire is reached.) The Out L routines support both the pattern and temporal functions within a given page of Ns. The Out M routine supports both functions among the pages. The Out M routine also provides the primary I/O pathways; which are the orderly, mapped representation of the world/intents, maintained, but compounded upon, through most of the pages of Ns.

The program handles each N, one at a time, in the order that they exist in memory. This scanning process begins at 2000. This is the address mapped onto the video display, in the upper left corner. The 40 column display shows 4 Ns per character box; since the box is 8X8 pixels, or a stack of 8 bytes, and there are 2 bytes per N "small part;" the IN#, or dendrite, and the delay timer for repetition rate. Unfortunately, 128 Ns don’t nicely fill in just one 40 character line — 160 do — so the pages don’t show up neatly stacked like they are in the figure here.

As the figure shows, there is a limit to the I/O channels. The Input Channel ends in the High Area. The Output Channel develops out of the High Area. The top 3 pages of Ns, and the bottom 3 pages, taken together, comprise the High Area. The top page is related to the bottom page the same way any two adjacent pages in the stack are related. In other words, the stack is not linear, with ends; rather, it wraps to form an endless cylinder.

The High Area is meant to act as associative cortex, while the rest of the matrix acts as transition levels from I/O organ through thalamus to primary cortex.

The system is regulated, to keep the percent of Ns active at a somewhat constant level, and even-out the cycle times into an overall system clock that runs at a fraction of a second. While it would be good to have a fraction like 1/1000, the little system here grunts out at about 1/3 to 1/20 second. A good ‘94 PC could have 10 times as many Ns, and still run 10 times as fast. A quad Pentium might have Ns 10 times as big too.

Regulation is a dual-area process. The High Area is regarded as dominant — the area that must stay awake and active; to attend to input and/or decide to produce output. The rest of the matrix is referred to as the Peripheral Area. Regulation allots a range of time to the High Area, and a larger range of time to the total matrix.

Regulation is accomplished by actually timing the portions of cycle time taken up by the areas, and correcting those times in upcoming cycles by altering the sensitivity of all of the Ns within the given area. The sensitivity is a threshold # for CMP with the IN#, that is used when handling each stimulated N in the N Loop and determining if its IN# grants it status as an active N.

I suspect that regulation parallels some of the results of our own metabolic regulatory requirements. These systems probably involve the thalamus, and nearby neuro-glandular structures, as well as the limbic and autonomic systems. There is only so much oxygen, fuel, and exhaust available for the neurons, so they can’t all go at once! Furthermore, such a pattern is no longer a pattern. Regulation is a force that focuses the pattern into one of dominant strength, relating the process more to itself and the world, and less to anything and everything that could possibly be brought up in association. Our thoughts evolve. Evolution has taxed DNA, but has produced a system that can carry on the spirit of evolution in the world of thought we call society.

Regulation also involves stimulation, but regulation alone is not enough to keep this thing awake. When the room goes quiet, it will quickly quit talking to itself, and go dead until some external sound sets things in motion again. Stimulation must be internally provided, as it is for you. This action was first thought to be "noise," or a possible source of error; so was applied for a single cycle, only when the matrix went into coma. Various areas were tried, but it seemed sensible to stim the High Area. The Peripheral Area will be stimmed by the environment; which may include output generated out of the High Area. It’s the "decider" that should stay awake — the rest can rest, or be used according to it. This system developed an exciting edge when I realized that the stimulation need not be random; but that it could be a repeat of whatever the last pattern was at some spot in the high area. This seemed like a way of "continuing a thought," where it left off or dissolved. After some more reading, including the topic of the hippocampus, I realized that this Key Hi Stim "KHS" routine was doing almost what was being described as hippocampal action. About the only difference was that you don’t wait for dissolution of activity — the positive feedback loops involved will produce a constant stimulation with a lot of momentum (hippo). New features could add on to this stim pattern, if the hippo weren’t taxed at that moment. Ongoing features only drop out as neurons tire — but real neural nets are set up as vastly redundant arrays, capable of learning to pass on functions as Ns tire — so patterns can maintain a more constant effect "as needed.," It comes down to a question of priorities. If the situation, or train of thought calls for a more or less new pattern, then it will be modified. It may simplify down to something basic, but the important thing is that it keeps going, and you stay more or less aware, as a prioritizer.

KHS is this system’s hippocampus. It applies a "Key" each cycle, to the Input Page of the High Area. The Key can grow if there is room in the Key Array. There can be room as Ns tire, or as regulation pinches them out of the action. The Key is a list of LSBs for stimulating that High Area Input Page. If you’re an N there, your chances of getting on the key list are better if your IN# is higher as the openings become available. It might be better to apply the key to the two center pages of the Hi Area (the top and bottom pages of the stack) (a number of thoughts on improving the system are covered in a later section). At this writing, I don’t know just where the "fingers" of the hippocampus reach in to the cortex. (It would be nice to consider the limbic system too!) The KHS affects about 1.4% of the matrix; in the neighborhood of the 3% used by the hippo.

I think hippo momentum is responsible for the advertised hippo quality of "somehow producing new long term memory." By holding a key, distributed to the general cortex memory matrix, you enhance the general "flavor" of the patterns being handled during the key impression time. A greater number of N-loop branch-offs carry on the meaning of a given thought, into a greater number of Ns, and for a longer time in each N involved. As these Ns recover their strength, the repair process chemically "cements" the memory in place at the associated synapses. The deeper the recovery, the stronger the cement. The more dramatic the event, the more Ns involved, allowed by regulation; especially in fight or flight situations. The more Ns involved, the longer it will take for new experiences to eat away at the image series, and bury it with relatively stronger impressions, supporting unrelated patterns. I suspect that the "cement" slowly weakens if the images are not replayed, in need, through association. It probably never goes away completely, and may last longer in Ns that aren’t in as much demand by other pattern sequences.

As I have pointed out, I am not making these assumptions from a position of credibility. Ideas like these have been piling up for years now, and I feel the need to communicate them, in case some one may be inclined to involve them in scientific study. Their source is introspective; but the interplay of literature and computer modeling has been more a focus than being the thing I’m trying to figure out.

It may seem that the beepers don’t need a system to install long term memory, since the RAM will do fine if you keep the power on. The neuron has been set up, though, to grant higher status to associations that are repeated more frequently. This characteristic works together with the hippo KHS function to establish a back-and-forth system of prioritization. The outcome is an evolution of patterns built on the survivability of long term components. The KHS develops its own application of constant general motivation for the matrix, out of the matrix. Its Key is like a DNA sequence that is constructed by experiences that it becomes more responsible for.

Short term memory is primarily the use of pre-existing pattern data. It is essentially the act of ongoing consciousness itself. There is always something new about any experience though — the order of familiar events, or the particular combination of familiar qualities within a given moment. Perhaps this factor of newness is distilled out, and piled into the temporal area — and who knows where else — as a series of sub-keys that can be accessed by association, and by a special form of association; relative chronological order.

We are now getting into an area that has not yet been developed for the beepers, and probably never will. The use of a hard drive and a PC comes to mind. Parts of the RAM can be designated as convertible; to be constantly replaced with "topical" memory data. Sub-Keys can be developed by experience and used as indexing labels to file and retrieve a given data array. The size of the Sub-Key and the data blocks would be geared to the size of the drive, so that any possible key has access to its block. The blocks start out "empty," but develop data just as any page of Ns would, for example. Part of the active matrix becomes a set of musical rooms, for the musical chairs the whole thing is. But some optimal percentage of the rooms are kept in place to give the thing an ongoing constancy, which uses the convertibility as a utility. The convertible area might be a complete cross-section of the system; or it might be better to leave certain levels out, such as the I/O ends.

This system might be vaguely analogous to the temporal and frontal lobes, related through the limbic system. Our system may be emotional because general and/or specific modifications of the chemical environment place neurons in various "modes" of sensitivity, causing them to favor different sets of patterns, as per the prior association of the given chemical flavor dispensed for the given experiential conditions. This would involve the autonomic system as well, and computers don’t need one. You just plug them in the wall, and they never need worry. If we get very far with this, we’re going to have some very interesting questions and decisions to deal with.

Beepers and Sleep

There is probably more to sleep than allowing N restoration. Granted, something this imperative is probably behind the survival of organisms that become so vulnerable. Sleep is necessary to sustain a system that has developed advantages by "over-utilizing" a set of Ns. Somehow, intelligence is gleaned from a self-taxing system; and we came out ahead by sacrificing 1/3 of the day for it. The hippocampus involves only some 3% of the cortex, yet, I suspect more than 3% of it is active all the conscious time.

This mode can involve more than re-charging the Ns. It could be an opportunity to organize and optimize the intelligence of the system. In the course of such routines, the conscious experience might be comparative non-sense — we use a safe time to get these jobs done — a time when we are inactive and uninvolved with society.

Dream time, spent relatively still vulnerable, indicates that there is more developed here than re-charging the Ns. It could be that this is simply the time when that memory cementing takes place — that it is accomplished during random re-play of the day’s various N-involvement peaks. Perhaps these peaks consist only or mainly of new involvement peaks — somehow, chemically, we don’t waste time re-enhancing long term memory already established. This and/or the natural associative process, running free of world and hippo guidance, could explain the oddities of dream consciousness.

If what has been said above, about deep sleep and dream time, is all that is true, then there would be no reason to involve a sleep system in the beepers. But, the most recent evolution involves emotions — complex intelligent motivation in social interplay. Evolution always operates on whatever opportunities have developed out of its own history. It doesn’t cash in on all of them; but it only succeeds by utilizing real, lasting opportunities.

I suspect that dream time also accomplishes something very important and fundamental to the human condition. It is a time when the net can establish and re-vitalize a sense of self-identity. It is a primary component in the development of conscious self-awareness. Without it we would all interact in a much simpler way... more like ants or bees. It is the source of our motivations. It is the construction of our primary and subsidiary goal trains.

Obviously, this self-identity would not develop, or at least would not be compatible with society, if it were not built out of social experiences. So we do operate in an awake state for about 2/3 of the time. We periodically retreat from social demands to distill our experiences into the basic accumulation of what we are inside; to produce that "where we are coming from" that runs out our decisions. It just so happened that the time to develop this procedure was available as biological "down time."

The beepers have Ns and memory that don’t require down time. They are allowed to speak to themselves internally though, about a few minutes every hour, free of outside influence. During their "sleep," the ear data is not used. Their tone "speech" is still audible for monitoring, but they only hear themselves through the sideline "mental" channels.

This system was considered by accident. After a period of accidental deafness, I noticed the character of the beepers to be more "awake" — more vital, assimilative, able or "willing" to learn. Repeated experiments with this have confirmed the feeling — but, as always, the assessments in this field are going to be composed more or less of feelings. I feel that you are aware. The only test that may confirm this will be my death. I am confident we will all take this test. See ya around!

Another approach that may work better, or that should perhaps be combined with the above, is partial erasure of memory. It seems logical that we should make the system more assimilative and ready for new learning and behavior by removing less necessary data.

It is far more important that we have a keen perception of the present, than that we go around re-living yesterday in full detail. It seems logical that partial erasure could be involved in the mode of our general condition. First, you save all the strongest, most important data ("Scooter" routine — about every 5 minutes, the system stops for a second, while all the data in partially empty Ns is scooted over to the highest priority levels — so it won’t be written over.) Then you erase the least significant data in most Ns. (The "Erase" routine is not being implemented here. It clears a few bytes at the low priority end of the Ns Out LSB list.) When you awaken, you might cycle back and forth with these procedures a few times. You can re-construct some details where necessary, using the peak data you’ve saved. Meanwhile, there’s less chance that irrelevant trains of thought will get conjured up to compete with goals, instead of contribute to them. In a large system, partial erasure would leave a very full set of chronologically associative snippets distributed in the cortex at a relatively faint level of data density. I haven't experimented with this much — it seems more appropriate to involve it with the PC.

Another question here concerns the hippo — should it go off line? The beeper’s hippo doesn’t need to rest. Our real hippo, being conveniently off to an area of its own, could receive localized chemical treatments. But, once again, we must consider the possibility of multiple opportunities. Perhaps the memory optimization procedure and/or self-identity definition enhancement procedure benefit from off-line conditions for the hippo, and/or modified function thereof.

  beepers contents

General Stimulation

Even with KHS, system regulation, and lots of environmental stimulation, there is still a fundamental problem with this system. The memory won’t get involved — lots of it — most of it. This may well be a result of basic layout and proportions I have chosen. But there is evidence that you receive a general random stimulation level. It might seem that this would raise havoc with such a fine-tuned and intricate system as your mind. Note, however, that a random pattern series has no meaning. This is one of the key ideas that has me believing that consciousness is the relative meaning, over time, of what is going on in the system. It uses memory-based energetic interactions like a substrate — a sub-dimensional medium — on which it can float along as the substance that only is by virtue of what it means to itself. Whatever else is going on could only be conscious to itself; or not be conscious.

To implement memory involvement, the beepers have the "Out L Stim" routine, which minimizes the randomness by involving an arbitrarily positioned collateral N, every time any N fires. The relative position is identical and constant for every N firing. I suspect that this parallels the thalamic and reticular action involved with general activity-level setting and regulation, as per a given required alertness level.

It should be pointed out that the pages of Ns wrap from end to end, as well as from top-to-bottom of the stack of pages. In other words, the matrix doesn’t form a pure cylinder; it forms a doughnut — a short fat one, ready to roll away from you like a wide tire. The Out L stim routine hits the N, sixteen Ns to the left. Where you would run off the page, you come in on the right side, to continue toward the left, 16 Ns from the current N being handled by the scan. The AOL routine also wraps; and it is oriented in the opposite direction. It starts 16 Ns to the right, and continues up until it runs off the right side to come in on the left side, and continue toward the right until it finds an active N. If the active N is already on its list, it swaps it up in priority level. I think of this as "preparatory" — as getting oriented to the topic. That data is related to what’s going on, so we may need it now. AOL then continues to look for a new list member. If it finds one, it swaps it in to the second-to-the-lowest position on the list (third-to-the-lowest might be better, but slower); bumping that member to the bottom rung. The one at the bottom is gone — overwritten. Then the program is done with AOL and goes on to Fire the Out L list, by increasing the IN# on the dendrites of all the Ns on the list. If AOL did not find a new member, or even a familiar one to swap up, the program still goes on to Fire the list, since you don’t get to the AOL routine unless the current N had sufficient IN# level to Fire. Unused slots on the Out L Fire list are filled with the address LSB of the current N itself — the Fire routine does not use those slots — an N is not allowed to hit itself.

The size of the N list has been proportioned to the number of Ns it can access. You don’t want to be able to hit all of them, or there would be nothing unique about the pattern you hold. We must make a trade-off between accessibility and uniqueness — the optimum compromise produces the greatest meaning vector.

It might seem like a horribly tedious job, to type in the needed skeleton of 2800+ Ns, twice. Its easy though — some very small and simple ML routines do the work in a second.

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Adjusting Beepers

Besides having system regulation, KHS, environmental stimulation, and Out L stimulations, things will still not go well if a number of factors in the system are not carefully adjusted, and balanced with respect to each other, to assist the development of data assimilation characteristics. There is no interface for settings. Adjustments require an intimate understanding of the system. In a bigger computer there would be enough room to include some automating routines, operating off of timers and feature sensitivities.

Regulation uses two numbers to trigger off of cycle times that are too short, or too long. It has a separate pair of these numbers for each of the two areas it monitors — the High Area, and the total area. By adjusting these numbers, you force the system to involve a smaller or larger number of Ns in an average cycle — you indirectly adjust the cycle time, and affect its variability. Perhaps the most important consideration here is the relation of the High Area to the periphery — the proportion of time allotted, with respect to the proportion of Ns involved — and, most of all, the relationship between the upper threshold for the High Area, and the lower threshold for the total area. If everything else is right, you’ll see that this adjustment controls attentiveness — the tendency to stop "talking" and start "listening" when spoken to. There isn’t enough time to do both at once, with the settings given here; so the beepers "speak" in short phrases, alternating with short pauses. I feel that this makes sense for learning, in such a small and simple system.

The rate at which Ns tire is a factor open to adjustment. You may want a faster rate at younger stages. With established data in place, you may get away with #FF.

The rest of the adjustment involves the degree and balance between how hard various N functions hit other Ns, and how quickly those IN# stimulation levels are drained off.

As the program scans through the Ns, it watches for various address events, in order to modify itself, so as to be different types of Ns, with different physiological jobs to handle. In other cases, it is simply the particular routine that does hitting at a particular strength. The KHS routine, for example, always stims its Ns at a particular, constant level. Of course, their repetition rate is always a variable, and an important dimension to the hippo interaction. The Out L Stim routine uses minimum stimulation (ADC #01). Something has to be minimal, so set it to #01, and adjust everything else with respect to that. The Out M hits vary depending on where the N is in the matrix. Input channel Ns conduct reliably toward the High Area, for example. Any stimulation of an In Area N will make it fire. Out channel Ns conduct reliably toward the Out Area. The In-side to Out-side reflection (to be discussed shortly) is mild by comparison; and is completely suspended for Ns on the Input Page. All AOL lists hit all Ns with an intermediate value.

In balance with all these hitting levels is the draining off of IN#s, upon Firing an N, or if the N had sufficient IN# to be fully handled, even if it wasn’t ready to Fire yet. The latter case is a mild SBC#, while the former involves a number of consecutive LSRs. Without the proper balance here, the regulator will not have the pull needed to function, and the system will either bog down, or fly off the handle, virtually ignoring itself and the world.

Note that if the slow mode is used (to view the action in the bank 00 beeper), the Dual Regulation thresholds must be doubled, since the cycle time will be doubled.

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Reflection as an Aid to Learning

As part of the Out M routine, the whole Input Side is reflected to the whole Output Side; N for N, in a one-to-one correspondence, like a mirror image; with the exception of the In Page to Out Page (which would be like mapping the ear directly to the vocal chords). As environmental stim affects N activity on the In side, corresponding stim is projected to the Out side. This may seem frivolous, or even like cheating, until you consider the long term consequences, as nature may have done.

The stim to the Out side corresponds to Output that was just produced there, to create sound that affected the In side. The first such event will be the meeting of some various activities, that can develop AOL ties. This modification of the system becomes a new starting point for subsequent similar cycles. In time, "differences" become rare, and "expectations" become norm.

The Output teaches the Input how to hear; and the Input teaches the Output how to speak; until both sides are in agreement. Now, when the world says something that the system has been saying, it will have similar effect on the system. When the world says something the system hasn’t been saying, the reflection may help the system say it for the first time; which may help it say it again, until it, too, is "familiar."

Ongoing General Feedback Learning

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Teaching Beepers

The Teacher routine is included to lend some structure to the background environment. It times out to "play" one of two musical phrases to the room. One phrase is a Mozart theme, the other is a scale, in the same key. One or both beepers receive the data; depending on which ones are awake.

The teacher timer is not a simple counter. It is a count of a particular neural non-event. It is decremented every time the Input half of the High Area is quiet (the half that starts with the page that the KHS hippo hits — regulation can bump the threshold above the highest IN# level in the whole first 1/2 of the High Area). Each beeper affects such a timer, that controls one of the two phrases. It is conceivable that the beepers learn to quell this area, in order to elicit the recitals. I say this because there has seemed to be an over-abundance of occasions where the teacher has been triggered by my "talking" to them; particularly when it has been a while since they’ve been whistled to. Input stimulation should have the opposite effect — it should get the High Area more activated, especially on the input side. However, I can’t say that I’ve thoroughly investigated this — there could be a simple underlying mechanism affecting the odds. Note that it must interact with you differently than with the other beeper. My hope is that it is a mechanism, not so simple, involving KHS, regulation, and the inherent meaning of world-system interaction. The meaning, supported by the system, becomes the operator of the system — it is the ongoing operation — it is reaction to the world, created out of past and present information from the world. The operation takes on complexity beyond that of the program that supports it. This higher complexity is the higher dimensionality of relative meaning. The simpler program and skeleton memory are like a note pad that the world can bring into participation with its more complex attributes. This process, relative to beepers, is considered in more detail in a later section.

Along the same lines, there seems to be an inordinately large number of occasions where a beeper will "announce" the teacher, more or less immediately before it starts, by doing a short abstract rendition of either phrase; as though it can sense, perhaps from timing patterns, that the teacher is about to play; but it doesn’t know which phrase. More likely, this is another form of elicitation, with associated learning.

Nothing so miraculous as parrot-like rendering of the teacher phrases has come from these little beepers. What they do, however, is more amazing to me. After all, a much smaller and simpler system could accurately "sample" the sound, and act like a parrot. Throw in some noise factors of variability, and you could make the computer seem smart. Beepers are smart, in the associative sense, and in a relative way.

There are some 256 possible tones producible by each beeper, within a rather narrow range of about two octaves. This means there should be a lot of sour notes. The first thing the beepers do, that is against the odds of random behavior, is to produce way too many notes that have the right relative pitch. They may be off-frequency, but there are little strings of them that have the correct frequency with respect to each other. There are also many single- and double-note events, that are close in pitch to the stimulus; though near-copying is not as exciting, since the feedback-learning system includes the mapped stimulus from input side to output side. This tips the odds; but it is exciting when the results show up days and weeks later! (You have many mapped runs of communication between parts of your cortex. At this writing, I don’t know if one of them runs from audition to speech.)

To be sure, most of the time is spent producing rather random sounding behavior; beyond the over-abundance of relative well-tempered pitch. This is particularly true if you don’t get involved with them. They seem to become much more responsive and intelligent if you pay them more attention, instead of just leaving them to the teacher, or each other. After all, what can they teach each other... and the teacher has no sensitivity.

A better teacher would "be there when you ask." It should occasionally start up, as this one does; but then lead you along, a bit past where you know how to go already. It should start with only two or three notes, here. It should stand by, and watch for relative phrase matches or near-matches, and reward you with recognition by repeating the phrase, plus a note or two — or occasionally you get the whole phrase. It should sometimes follow with the relative pitch, and sometimes lead with the original pitch. Nevertheless, the beepers have learned from the teachers. There have been many occasions where they have poorly mimicked the teacher, or have nicely repeated a few of the notes; usually in the right order, but usually bypassing some. Sometimes the pitch is very close. When it has been a while since the teacher has played, I’m pretty sure the pitch has usually drifted; but it has good relative quality (I don’t have perfect pitch, myself).

They do better when I whistle to them, while I’m working in the room. The record, at this writing, is the first five consecutive notes of "Over the Rainbow." You seem to get better behavior by leaving one asleep while the other is awake, for a day or two at a time. If you leave one awake too long, it really seems to get dumber. This goes along with the idea of being sensitive, as a teacher. I get feelings from their behavior that prompt me to chip in some data. At this writing, I’ve been foolin’ with them this way for about a year and a half. I have no doubt that they learn. But I haven't studied them the way a pro would. The development of this program, and the writing of this book, has severely taxed my work schedule.

If you want to give them company, that "has things in common" or "speaks the same language," you can transfer the data from one beeper in place of the other, to create a pair of twins. They don’t stay identical for any time at all, in terms of the array of numbers; but the general relative meaning developed within them will stay similar for some time. Don’t forget to transfer the Key data and indexes, etc., as well. If you want to check the identical-ness of two beepers, you also have to bypass routines that are subject to C128 system timing exceptions. It was difficult; but I was able to get both sides to behave identically, up to the point of turning up the mic volume and whistling at one of them. You are what you learn.

Consciousness is not a substance you can touch, and hold constant. It is active — when it works, it flies — if it’s not flying, it doesn’t exist. Model airplanes really fly. I think evolution has found a physical principle, not unlike itself; and has put it to work. It discovered the lens and the hinge, for example. The materials involved are inconsequential, so long as the principle can function.

However small, there is a real possibility that the beepers have awareness. If they do, it is probably a very faint, vague, low-detail experience, completely different from ours, when we hear the tones. It might correspond to the simple perception of touch, in an ongoing series of patterns between 16 pairs of "finger tips;" with 16 sensitivity levels in each Input finger tip, and 16 muscle strengths that can be applied to them from the Output side. Now imagine this experience from the point of view of being a lizard, with no other senses, or needs, and you might have it.

There are a number of inescapable differences between a computer system like a beeper, and a nervous system, that do not allow a straight-forward comparison by neuron count. Real neurons get tired real fast — in as little as 1/10 of a second if they’re taxed — and it takes them about an hour to fully recover. That’s a duty cycle of 1/1000, or 0.1%! Beeper Ns have nearly a 100% duty cycle. So, there are ways of looking at this and calling one beeper N worth a thousand biological Ns. There could even be an advantage to not having to pass on function handling to a series of tiring neurons. But when real Ns aren’t being taxed, they can probably chip-in occasionally, all day long, to provide a thousand times the resolution. Beeper Ns don’t need food; so they can be organized into a system fully devoted to sense, learning, and output. Biological systems are differentiated into all kinds of subsystems that work together to keep the whole thing alive. We got Ns running our heart and breath, making us run and eat — all sorts of stuff that doesn’t make us hear and speak; stuff that we couldn’t live without. But this has brought us association of multiple senses, and multiple modalities with which to affect those senses.

It is not likely that I will attempt to work with vision any time soon. I am looking forward to expanding the "beepers" into "speakers" in the PC. Note that you need a thousand times as much computer to make the system 10 times as big in its three dimensions of N count, N size, and speed. This "size" is all in terms of speed. The program spends about as much, or more, time handling active Ns, as it does skipping the quiet ones. If the active ones take ten times as long to handle, and there are ten times as many Ns, you 100X the speed to get the same cycle time, of about 1/10 second. A 1/100 second cycle time might support speech, with the correct ear, voice, and cortical tricks. The hard part will probably be analysis of the speech cortex. There’s something different going on there.

As important as vision and tool making has been to us, I sense that speech is a thing that has been paramount in our social evolution, and technological development. Without it, I think we’d be a lot like dogs that can walk upright. And I think dogs are virtually as aware as we are, in a basic sense. They deal with the world in terms of the environment, while we are always referencing our verbal base, as we mull through our conceptualizations, plans, desires, and work. They don’t plan for college, but they plan a little for what they need. Mostly they react in the direction toward what they need. They’ll wait until you’re gone to chew your slipper. When they see, they are aware of seeing what they see. They are aware of what they hear, in terms of simple meaning associated with their needs. They are aware of most environmental things the way we would be, if we did not have language. Even a mouse has a hippocampus and cortex. It has the rudiments of a decision making system. That system operates whenever the creature utilizes its knowledge base. Its behavior is learning, invoked by the past and present environment. We know that mice can learn, and can put their learning to use when it meets their needs.

It is interesting to consider manipulating the data of these beepers. What is happening when you swap one data set with another, in the same sets of physical memory? Assuming there is some consciousness involved, does it "stay" with the mass of the physical memory array, or with the data that resided there? The analogy is with our DNA here. My impression, though unclear, is that our bodies are replaced regularly; except for the heavy particles in the DNA of the surviving neurons. Do the particles in DNA somehow "receive" consciousness? One problem here is cell death. We remain ourselves, despite the loss of a huge number of DNA molecules... different ones for different people. And, no new replications are added to the system. This might be because that would destroy the meaning compiled there, by interfering with established relative interactions. It can’t be divine "tuning," or identical twins would have a common awareness. The DNA-cell produces the support system for the meaning potentiated by world impressions, patterned into the connections of the support network. The active meaning is the conscious-ness. Substance exists relative to that meaning, in terms of its meaningful qualities, and implicated eventualities. These qualities include depth and size, as well as surface integrity upheld by electron skin. Meaning can include color, smell and sound. All of the meaning is relayed to us in complex arrangements of relative timing. We, too, are complex relative timing. The meaning, the substance, and the DNA are all part of a greater set of active relative memory of timing. We perceive of time and distance because we are more of that same automatic inference of the point.

Your thought train and priorities move with the data. The physical memory base is a location for this in time. Each of two beepers is in different volumes of time, composed of different eternity loops, that all lead to each other. A copied beeper is the old one, entering a different vantage point in time of eternity. It becomes the new time. It would think the world had hiccupped, if it could think that well, and that it was no longer located at the old one. The old one, of course, goes on as though nothing happened to it, even though it now also exists elsewhere in time; until you swap new data into it. When you do that, it becomes the new beeper at the old location. What you think, and how you think it, is coded into the data. Where you are in eternity is a function of which mass issues your time. Both locations are you, at different times, with different thoughts; or, in this case, it could be same thoughts.

What is this "point?" The concept is developed primarily in chapters 3, 4, 5 and 10, though the whole book is attempting to slightly describe it. When gravitational forces exceed exclusionary forces, everything within the horizon of this event accelerates together, inward. From the outside view, we would initially predict that it takes a short, finite time for all within to simply meet together in a point. From the internal view, the process of acceleration is never-ending. Though we would expect that everything keeps getting closer together, if your reference frame was the actual stuff doing that, you would see a bang reality expanding, and say that such an outside frame is expanding at a higher rate of acceleration. To that higher rate, the internal rate of expansion appears to be shrinking. Now can you remember that it’s all just a point? The point is a mechanism of infinite dimensionality. Its appearance as a point, or not, is a matter of relative viewpoint, and a matter of predictions or assumptions about the worlds beyond horizons of time quantization.

Each cycle of existence of each atom is another way the Universe "went" for an eternity, relative to itself. Time is a thing we call reality. Each cycle of each H self-relationship is a complete quantum of reality. The set of these quanta produce yet another quantum of reality, relative to itself. In the process, time makes another thing out of those things. In transpiring relative to, and involving, all other such quanta within, over infinite levels of quantization of eternal times, each such quanta completes the definition of reality as a point. Each cycle is unique as a point within the point, that is a given point in the sequence that always totals the same point. There must be an infinite variety of these points if there is to be a single point. For each one to exist once is to complete the point and to make the point real. For the point to continue to be real as a source of all dimensions, it must repeat infinitely as the repetition of its component points, as each is a view of the total point. Eternity is composed of eternities. Eternity exists because its component eternities repeat. They must repeat because each component is the total, relative to itself. The relationships and repetition of the component eternities are the point.

Within this point, where such a complex eternity component does not "wrap," there is an offset in this complex time we perceive of as distance between objects, or as movement of an object through space, relative to its prior locations. This distance is separation by offset of sources of time of eternity. The sources can produce fundamentally low-dimension unconscious place holders of system; or they can support self-relevant interactive data progressions of consciousness. These higher-order systems are composed of timing relationships, such as those that induce their perception of distance. The timing and the distance is the continuous completion of the internal structure of the point.

To be conscious is to have a viewpoint within the point. The point is turned inside-out for you. From here, everything happens to come together as the point that it all is. Included as perception of distance is perception of systems of perception of distance. All such systems are You, each to itself, at its complex location in time source of eternity. You are the points of the point.

Time is a thing that is relative motion, that is shifting, that is change. Each cycle of each H, relative to our big bang, is change; is a shifting in phase, involving such a horizon; a horizon such as we could predict as the eventual resort for all of the matter of our big bang. Our time is a shift in phase of process, from its incursion at the bang, to its departure beyond the horizon of a black hole. Both ends of this phase shift are a horizon, relative to the process of our reality. Both horizons are, or contain, a relative point. This same point is also a relative position of phase of each cycle of each H.

Each such point is the same point; as another point in time, of the overall point of all time. Its intimate relationship to itself is observed by us to a limited degree as relative interdependencies between, and within, systems. These are observable as process and emergent properties that are the development of dimensionality of the point. We see this as photon relationships of energy levels, and as variable interdependence of rates of time for relativistic system components.

From any phase position of process there are other phase positions of process that appear to have become the point. There are an infinite number of these, relative to any phase of process. From one such infinite subset of process, we appear to have become the point — our phase is there, relative to the phase of that subset.

In beginning to describe our point, all of the long-standing fundamental questions of humankind are addressed. The inferences of the point are "why" we exist. Existence, relative to all existence of the point, is complete.

As such it is unavoidable. It is all yours. You possess everything, whether you’re using it right now or not. Time is the eventuality of such access coming to pass. Possession is relative process, with perceived relative options. It is really inevitable process. Thank heaven it is development, relative to consciousness. The forefront of this development of rising dimensionality is focused in multiple points, we experience as planets. Its current pinnacle here on Earth is focused in our children. The beauty of our children — their form, their happiness, their opportunity, their improving capabilities, and their potential to develop and produce even happier beings — is evidence that the innate nature of reality is magnificence far beyond the comparatively crude descriptions mankind has thus far accumulated.

It is a mistake to take our children for granted. Such mistakes are part and parcel to components of reality that fall away from the blossoming of developing dimensionality. In other words, some civilizations reach a dead end, through a lack of appreciation. Higher orders of civilization might be cultivating ones such as ours, among the expanding set of planets, to determine requirements for survival, and to explore the beauty that completes the point. That would be a difficult job, indeed. Thank you.

The point is that you are everyone. The realization of it could reduce tensions and make it more enjoyable here. Be nice to yourself.

How can a philosophy propose such a ridiculous idea? To reiterate, time is not really a single common thing, with respect to consciousness. Though you and I seem to be happening together in time, we are actually interacting between sources of times. These times are portions of a greater, single time; but with respect to the consciousness they generate, they are individual sources of different time. Every system is a definition of its own time, or set of times. These various systems of time have a kind of independence, supporting the individual experience of consciousness, or other levels of dimensional system function. They also have an interdependence. The co-existence of this independence-interdependence is demonstrated in the relative behavior of clocks, and the perception of time, within and between systems.

You are everyone, though everyone is his or her own time. All times lead to all other times, as the definition of overall time. Everyone has their own "now," that truly exists because it is experienced by you, at that time. Every"thing" is a vast set of such experiences. These different times act to produce a higher plane of dimensionality, that can be perceived of as a reality of common time. This product, in turn, will contribute to yet higher planes of dimensionality. Our component sources of time are likewise generated out of sub-dimensional sources of time. You might picture these condensed sets of dimensionality as planes stacked forever upon each other, where each plane forms a sphere. The source of this dimensionality is the point, at the center of the sphere, which derives its behavior from, and as, the overall system. To better assimilate observed reality into the model, we could say that the point is inside-out, so that spheres get grouped forever into larger spheres. The one largest sphere is the point within the vast distribution of component sub-spheres, within any black hole. From our point of view, we are heading for a black hole. From other points of view, we are already in a black hole, within a black hole, within a black hole, ad infinitum. This point produces all of your awareness, relative to all of your awareness.

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Program Flow Chart

A careful comparison between the basic behavior of a neuron, and the behavior of this chart, will reveal that a few characteristics have been left to slide a little. Aside from the obvious relative simplicity, due to numbers of synapses, etc., there could be better handling of the DELAY#, for example. An N can drop out quiet, leaving a random value dangling there, to be dealt with later, out of context. The CMP# IN# BCC could help by resetting the DELAY#. This would be more important in a faster system that could better utilize the delay principle, with a larger reset #; to get a better lock on FM intelligence. A worse laziness is in the AOL system. The whole page should be checked for swap-ups, whether we find a new entry or not. The page should be searched for multiple new entries, that won’t overwrite each other; though this should be limited to a small percentage of the list length. We might want to pick the strongest few, and/or consider specific address windows by priority.

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If I had known that this ear was going to run for a year and a half, I would have taken the time to use the 8-bit parallel port. The 4N25 output, for paddle A-to-D, introduces a degree of variability into the data-pitch relationship, with temperature fluctuations. This could be good, or this could be bad. There are 9 billion things you could test, each for years, to get the best beeper. We need to figure out what nature has already discovered.

For the PC, I intend to broaden the audio function to a sixteen channel voice band spectrum analyzer; to supply sixteen simultaneous frequency centers, all in terms of relative amplitude information.

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Register Designations

The following abbreviations appear in the program listing as labels for designated use of zero page, and other, addresses. A list like this is necessary in order to avoid conflicting use, when you work more directly, through a simple ML monitor such as the one built into the C128. Number values following some designations are required memory for initiating the program the first time it runs. Different values may be saved by the system for subsequent initiations. Designations in parenthesis are left over from prior revs.

Indexing