Noble Ape Blog

The nalongterm command line program now includes a command called “epic”.  This lists the most talked about apes which currently exist in all of the episodic memories within the population.  The most talked about apes are not necessarily the same as the most honorable ones.  Who gets talked about depends largely upon the anecdote instruction (ANE) being activated within braincode programs.

“It allows us to do mathematics as well as language. And this system of taking discrete or particulate elements and recombining them, is what gives genetics and chemistry their open ended structure. Given this pattern, an interesting question then is: what were the selective pressures that led to the evolution of a recursive system? Why is it that humans seem to be the only organisms on the planet, the only natural system, that has this capacity? What were the pressures that created it? Thinking about things like artificial intelligence, what would be the kinds of pressures on an artificial system that would get to that end point?” – Marc D. Hauser

A key part of human-like cognition seems to be the ability to string things together.  This very sentence is a string of words, which also contains substrings.  As observed by Robin Dunbar, humans seem to be able to form chains of reasoning, as part of their typical communication “in the wild”, which are longer than may be observed in other primates.  Chimps can cognitively manage second order relations (theory of mind) but humans can comprehend fifth order relations, or more.  So I can think about A’s beliefs about B at time C and whether those were similar or dissimilar to D.  If you read any work of fiction, or just watch a TV soap opera, these strings of relations and beliefs are ubiquitous, and their interaction and resolution creates dramatic potential.

The question arises as to where these chains come from.  Currently I don’t think there’s any definite neurophysiological answer, but my guess would be that there is some mechanism which allows loops to form, and to maybe be recursive up to a shallow depth of about 5.  It could just be that some intercortical connection is thicker in humans, after a couple more cell divisions during development, such that it supports more back and forth re-entry in a cycle which can be of longer duration than a second order relation.  Quantitative differences in structure can sometimes lead to qualitative differences in function.

So a possible hypothesis about the physical basis of a type-0 language system is that it wasn’t really selected for as such, but is a byproduct of more cell divisions at an early stage of brain development.  That is, it could be a spandrel.

In recent years something called Artificial General Intelligence (AGI) has become fashionable, but the question of what constitutes a good design for a mind is actually much older.  So what is the most maximally general mind which could in principle exhibit any sort of activity within the constraints of memory and time?

I think the answer to this is fairly unremarkable.  It would just be a Turing machine.  That is, a program comprised from some instruction set, where some instructions exist which can write to or read from the environment, and other instructions which do things like adding, multiplying and moving data from one address to another.  Something like the following, where programs A and B are different individuals in a population.

These would be able to do anything which is computable, and when individuals met they could form a temporary shared address space which allowed reading and writing between them, like this:

Individuals might have a finite life span, and new individuals might be introduced with initially random programs as a source of new information, or novelty. Under this kind of system – which is not even as sophisticated as genetic programming – programs which are good at surviving in the environment (whatever that might be) and transmitting their data from one individual to another would tend to stick around and multiply.

At this point you could say that using a system such as this one the AGI problem has been solved, so long as you don’t believe that hypercomputation is an important requirement.  Even the limitations of Gödel’s incompleteness could be addressed to some degree if there is a population of heterogeneous programs, such that things not provable or complete within one mind could be provable by another with a different perspective – a triumph of overlapping capabilities.  I think that some Alife systems do work in a similarly general manner, and the above description is also similar to how the braincode within Noble Ape works.

However, there are some down sides to complete generality.  In a system where any kind of computation is possible it may take an extraordinarily long time to discover solutions which are in any way comparable to the kinds of things which when we observe them in the natural world we would describe as being “intelligent”.  Even for quite small programs and instruction sets, the space of all possible programs is going to be colossal, especially when they can move around between individuals such that they effectively span across minds.

In my estimation real intelligent systems, like primates or dolphins, aren’t completely general like this.  They come with a lot of preexisting evolutionary baggage, which constrains their mind architecture in a way which provides more immediate adaptive value for survival.  So in Noble Ape there are also other systems which are part of the mind design, but which are not Turing complete systems.  These are:

• The social graph, which stores information about other individuals which have been met
• An episodic memory, which stores information about events which have recently occurred
• The attention system, which can shift attention between entries in the social graph or episodic memory.
• A drives system, which attempts to keep some important parameters within reasonable limits.
• An affect system, which ascribes affective weighting to memories, depending upon their emotional impact

None of these systems are programs themselves, but the braincode system is able to access and recombine them in novel ways such that the mind as a whole is still a sort of Turing machine.  It’s this ability of a particular kind of language system to re-organize and transform existing legacy modules which I think is important in human cognition.  So for example if you’re reading a book which contains some new idea then areas from your visual system, audio system and higher level conceptual system might be re-combined in a new way, forming a new synthesis which can itself be remembered for future reference.  If the language system is recursively enumerable then an endless number of syntheses are potentially possible, even though the language itself contains only a finite number of words or instructions.  It also means that arbitrary syntheses can be generated, to produce imaginary scenarios which have never previously been experienced.

If you consider simple kinds of automata, like the ones described by Stephen Wolfram in New Kind of Science, and then if you consider the cultures of primates or humans to be forms of automata but just with many more dimensions then what kinds of automata would these be?

I think Wolfram does a reasonably convincing job in that book of showing – perhaps even to a gratuitous extent – that the classifications which simple 1D automata fall into are also applicable in higher dimensions too, such that they represent general properties of information systems as they evolve over time.

Class I

What would a class I culture look like?  It might begin in a random sort of way, but soon converges to a single highly stereotyped set of behaviors.  This is an “end of history” kind of situation, or a minimum information state in terms of algorithmic compressibility.  Many animal cultures do seem to be like this.  For example the social organization of bees or termites was pretty much the same 1000 or 10000 years ago as it is today.  Not much qualitative change seems to have occurred in the way that their cultures communicate and organize.  If you could compress bee culture into an algorithm of minimum size, that algorithm would only change slowly over long periods of time, mainly in line with underlying changes in genetics or climatic conditions.

Class II

In a class II culture you’d see oscillations in its behavior over time.  There might even be secondary oscillations at the level of communication between individuals, but these would be of a symmetrical kind.  A program representing this sort of culture would be a fractal.  Here I’ll go out on a limb and conjecture that most existing primate cultures fall into this category.  So you can have developments such as termite fishing, cracking nuts with rocks, washing food in the sea or bathing.  My guess is that these local cultural adaptations will wax and wane over long periods of time, but that they are non-cumulative and so don’t have any particular historical direction.  There are dynamics, but only within a limited range.  Possibly bird song might also fall into this category.  Classes I and II could be described as being steady state or equilibrium cultures.

Class III

A class III culture would be chaotic, such as during wars, revolutions or natural disasters.  I don’t know of any cultures which are perpetually chaotic or random-looking, although amongst social creatures ranging from insects to primates there are phases of unpredictable change as factions compete for resources or respond to environmental change, such as the disruption of an ant nest by a predator.

Class IV

This is the more interesting type of culture, and as far as I know it’s only possessed by humans.  A class IV culture exists somewhere between classes II and III.  It can contain cycles, such as the secular cycles observed in human history, but has a non-repeating and cumulative structure.  Crucially, these cultures can be Turing complete, and contain meta-machinery which is not simply symmetrical as a fractal would be, nor totally random.  Meta-machines within these cultures would be analogous to Ross Ashby‘s notion of “organisms”.

Some additional speculation

Conjecture I : “Interesting” cultures which can support advanced features such as folklore, art, religion or complex technologies are those which are Turing complete and can contain meta-machines.

Conjecture II: These cultures are a function of the grammatical complexity of their communications systems.

Conjecture III:  At some point in human evolution there was a transition from an equilibrium culture to a Turing complete one.  This I call “the computational revolution”.  Whether other creatures have also done this, such as cetaceans, is still unknown but it should in principle be possible to find out by studying their communication behavior.  After the computational revolution, humans became symbionts with their own meta-machines.

For a while I’ve been thinking about how to possibly implement something akin to a theory of mind, and now I have a provisional solution. Previously, when Noble Apes chatted they did so in the same way with different interlocutors, and for a primate this obviously isn’t very realistic. A better strategy, which allows for all sorts of devious outcomes, is to be able communicate in different ways with different individuals, and this necessitates having some kind of model, or at least partial representation, of others.

To implement this I’ve transferred the braincode programs from the noble_being structure into the social graph (social_event structure). The first entry in the graph is always the self, so this is the inner part of the internal dialogue with the outer part being stored within links to other individuals.

The idea is illustrated in the following diagram, which shows what happens when two apes are communicating:

Having the braincode attached to every link in the social graph does increase the overall memory consumption, but this change doesn’t add much to the CPU usage.  The blue boxes represent braincode programs, and when two programs are linked they form a temporary shared address space which allows data to move between them and for values in one program to become parameters for another.  It’s a very abstract representation of a language system, which makes no attempt to simulate individual words, concepts or articulations, but does allow for recursively enumerable grammatical structure.  The idea is that behavior may be observed which has a qualitative similarity to real biological language systems.

A Meeting of Minds

When apes meet for the first time the (outer) braincode associated with the new social graph entry needs to be initialized.  If there are no other individuals in the graph then the inner braincode is copied (a kind of bootstrapping effect, where you use yourself as a model for other conspecifics), otherwise braincode from the most similar individual in the graph is copied over to the new entry.  Similarity is decided based upon the friend or foe value, because this is initially calculated based upon a variety of genetic and learned parameters which could be called the prejudice function.

The Socially Constructed Self

This kind of cognitive architecture results in an identity which is socially and historically constructed.  When not communicating, or even when sleeping, the cognitive process of the ape becomes an internal dialogue between a number of different imagined actors, some of whom could represent individuals who are no longer living but remain persistent and who may continue to exert influence as informational creatures of the ideosphere.  Instructions within the braincode can trigger switches in attention between the different individuals in the social graph or between events in the episodic memory, and there is also an attempt to maintain a consistency of narrative flow such that the next focus of attention may have some properties in common with the current attentional content.

At the end of a lecture about the phenomenal self model, Thomas Metzinger hints at this kind of portable selfhood when he says “nobody is born, and nobody ever dies”.  It’s an idea similar to the Cartesian theater, but not quite in the same sense as meant by Daniel Dennett.

Some Implications

A couple of consequences logically follow from this sort of architecture.  Firstly, it’s possible that an ape could experience something resembling grief or estrangement.  When individuals are removed from the social graph this literally changes the cognitive dynamics.  Less controversial would be to say that an ape undergoes some psychological disturbance when they lose contact with another individual who previously played a significant role in their cognitive dynamics.

Another consequence is that fantasies involving beings who never existed could be supported within this architecture.  When spreading anecdotes during chat there is some probability of miscommunication or deliberate fabrication of information, and in principle this could turn into a persistent folklore or proto-religion perhaps similar to ancestor worship.

Also, although not currently implemented it’s possible to imagine autistic apes.  In this scenario there would be some limitation on the creation or memory size of braincode for each link in the social graph, with the result that the number or degree of modeling complexity of actors on the mental stage becomes more constrained, or reduced exclusively to the self.  A possible hypothesis about the rapidly escalating size of the human brain over its course of evolution is that this was a ratcheted response to a complex social environment where the ability to better model other individuals within the group had significant adaptive value, and with creative fantasies,elaborate traditions and religions being a byproduct of this.