Iteration – Variation – Persistence.

Paul Gilchrist 7-04-2016


Assemblies of matter can become ordered into systems whose behaviour may be non-cyclic or cyclic. Systems are subject to error that may become incorporated and persist as adaptations. In non-cyclic systems persistence is limited by the ephemeral nature of such systems. In cyclic systems the adaptive modification may be reiterated in each cycle of the system and thus be prolonged in existence. Ancestral cyclic systems have been subject to selection pressures leading to the emergence of complex systems including living organisms and their sub-systems including nervous, metabolic and locomotor systems. Ideas emerging in human central nervous systems can be expressed as memes within a culture and be subject to the same formula of iteration, variation and persistence that permits “descent with modification”.

It is my contention that the purported universality of Darwinian evolution is due to its being one form of cyclic system, in all of which operate according to the formula iteration – variation – persistence.


In our material universe, everything emerges from prior things. Everything is derived from interactions of matter and forces that have led to the formation of objects and their behaviour. Interactions between objects has led to the emergence of orderly systems including both cyclic and non-cyclic systems. The order in any system is established according to the information coded in its structure. Variation may occur in any system with consequential effects that may be negative, neutral or positive. Positive effects may persist and be adaptive.

Cyclic systems occur in sub-atomic, atomic, physical, chemical, autocatalytic and living processes as well as in processes invented by humanity. The operation of this process in pre-biotic conditions shows its origins. Of particular interest in living cyclic systems is the way nervous systems organise information in a cyclic fashion so as to form ideas which can be stored in memory or manipulated in cognitive processes and can be expressed as memes for further iteration, variation and persistence in our culture.


In the beginning it appears that there was a phase of potential energy existing in a state of inertia which tipped at the Big Bang into a new dynamic phase where matter emerged and was subject to inertia and momentum and “events” occurred.

The explosion at the Big Bang hurled matter off, in what could have been straight lines headed towards infinite dispersal. However the inertia and momentum inherent in matter were affected by gravitational, electromagnetic and nuclear forces. Gravity and angular momentum gave us galaxies, solar systems and planetary and other cosmic bodies which operate according to Newton’s laws of motion.

Matter coalesced, collided and persisted as assemblies that populate the universe. The interaction between the matter and these forces produced events that had a by-product we call time. The interactions led to assemblies with much in common but also with many variations. Some assemblies behave as systems.


A system:

  • is any assembly that has been ordered – naturally or artificially.
  • has structure and function.
  • behaves according to the coded information inherent in its matter.
  • operates within an environment that includes other systems, other material objects and forces of attraction and repulsion.

Order and disorder are central to the 2nd law of thermodynamics which provides that order inexorably changes towards disorder unless energy is captured and used in delaying that journey for a time. The move towards disorder applies fully to a closed system  (typically the Universe) while the temporary delay can apply in open systems such as those we experience here on Earth.

Inertia tends to give a degree of stability to matter and any of its assemblies, including systems. Momentum tends towards instability.

The balance between inertia and momentum can lead to behaviour called by Pross 6, dynamic kinetic stability (DKS). He discusses the general trend from less complex and kinetically less stable to more complex and kinetically more stable replicators. He extends the idea to populations when he describes ‘dynamic kinetic stability’ as applied to a stable population of replicating entities. The term ‘dynamic’ reflects the continual turnover of the population members, the term ‘kinetic’ reflects the fact that the stability of the replicating system is based on kinetic parameters rather than on thermodynamic parameters. It is the values of these parameters, together with the availability of resources, which determines the stability of the particular replicating system. Accordingly he characterises stable replicating systems (i.e., those that persist over time), whether chemical or biological, as dynamic kinetic states of matter. He says that the “utility and significance of this term can be more clearly gauged by comparison with the term frequently used to describe inanimate systems, the more traditional thermodynamic states of matter that characterize much of chemistry”.

It appears to me that this process is also characteristic of cyclic systems and is responsible for their persistence.

Pross’ contribution is particularly significant in that he is considering populations of systems albeit he is restricting it to “replicating entities”. My view is that all ordered systems or entities undergo a process of change that is subject to variations (errors) that may facilitate the survival of the system in a changing environment. I characterise this by the formulation iteration – variation – persistence.

There seem to me to be two ways systems can operate, cyclic and non-cyclic. Non-cyclic systems may have various pathways including linear, curvilinear, whorls, sigmoid, helical or fractal etc., but they all have an end point. Cyclic systems do not have an end point but operate as a complete cycle with the starting point, wherever that may be depicted to be, recurring in a cyclic fashion.

Cyclic systems have an existence or “life-cycle” while non-cyclic systems are ephemeral, having a term of existence or “life” ending at some stage, without restarting. Cyclic systems repeat their behaviour and thus achieve a sort of persistence or survival. This persistence is the key behaviour that enables survival of the structure and its function (or behaviour) and thus the preservation of key information embodied in its material structure. Both cyclic and non-cyclic systems may undergo enduring adaptive change but adaptations in cyclic systems can persist while those in non-cyclic systems are a more like acclimatisation or adjustment and are ephemeral and come to an end.

It is important to know which type of system we are dealing with because human intervention in a non-cyclic system has less enduring consequences than intervention in a cyclic system..


When a system is established, naturally or artificially, its stability is essential to its persistence or survival. Non-cyclic systems end, but cyclic systems repeat or reiterate themselves. A simple cyclic system does not multiply itself, it merely reiterates itself. A more complex a mechanism must emerge before a system makes multiple copies of itself. It seems to me that the emergence of the ability of a system to multiply b itself is at least as significant as the subsequent emergence of life.

A cyclic system undergoes repetition and each cycle involves an iteration of the information that constitutes the algorithm or formula that rules its process.

Matter can be ordered into various assemblies which embody information in their structure. The behaviour of any assembly is determined by the coded information embodied in that structure.

As indicated above, when assemblies of matter become self-organised we call them systems. A system may be cyclic or non-cyclic in nature. Cyclic systems share some common characteristics which I identify as the algorithm – iteration, variation, persistence.

Any cyclic system:

  • Repeats itself (iterates).
  • May be subject to error (variation).
  • May persist (adapt).The functional integrity of a system depends upon its structural integrity. Any change in its structure or behaviour may be corrected (either self-corrected or corrected by human artifice) or, if not corrected, it may be incorporated within the system. Any incorporated change in structure or behaviour of a cyclic system may be negative, neutral or positive in its impact. A positive effect may interact with the environment and lead to the emergence of an adaptive change that persists in further iterations.

Negative change leads to loss of order with consequential decay, decomposition, death or extinction. Neutral changes may be retained without affecting the behaviour of the system and may lead to the accumulation of “junk” or redundancy. Positive changes may result in the emergence of a new structure/function with the ability to survive in its environment.

A cyclic system may be influenced naturally or artificially by:

  1. Alterations in the frequency of iterations.
  2. Alterations in the frequency or type of variation.
  3. Alterations in the environment.

The process of iteration – variation – persistence is exemplified in Darwinian natural selection, but is not confined to that example. It applies universally to any change in a cyclic system. In Darwinian selection the substrate is the genome. Information in the genome is subject to iteration – variation – persistence. This is not because there is replication or reproduction involved but because iteration is involved and replication or reproduction are extensions of that process.

This pattern of iteration – variation – persistence seems to underlie change in all cyclic systems and to have led to the emergence of all the persistent adaptive systems we observe in this material universe.

Darwin 2 referred to “descent with modification”, which others (Dawkins 3, Dennett 4) have since spelt out as involving processes of replication that are subject to mutation which can sometimes lead to adaptive modification which may survive in the environment. Others (Campbell 1, Kelley 5) have explored how the mechanism applies more widely, even universally.

It is my contention that the universality of Darwinian evolution c is due to its being one form of cyclic system and thus it operates according to the formula iteration – variation – persistence.

This process has been studied in living systems and found to consist of two parts, the genetic code (embodied in the DNA) and the vehicle. The genetic code is capable of adaptation that may be inherited. The vehicle, the organism, carries the code through a period of time (development) from one replication of the genes to the next. Copying of the code occurs through mitosis in the somatic, non-cyclic, stage which may also undergo error/mutation but death of the organism eliminates the error with the death of the vehicle and the changes are mortal.

Cyclic systems operate in all areas including sub-atomic, atomic, physical, chemical, autocatalytic and living processes. Some (Randall 7 and Turok 9) propose a cyclic universe d.

It may be more than a metaphor to envisage an idea as an active cyclic system idling in the memory waiting to be aroused into action. If there is a massive storage of cyclic systems of nerve activity idling away in the memory, it is possible to see how an emerging “new” idea could stand out from the existing stored pattern of cycles and be recognised as something surprising and new.

Nervous systems organise information in a cyclic fashion so as to form ideas e which can be stored in memory or manipulated in cognitive processes and can be expressed and become memes available for further iteration, variation and persistence in our culture.


Because systems are susceptible to both unintended and intended human intervention it is important for us to be aware of the underlying mechanism. This is especially important in the case of cyclic systems in which the effects of human meddling are more lasting. The most significant invented cyclic system is the market. Some (Ridley 8) find support for pet theories in the story of evolution suggesting that outcomes are “in some sense vaguely progressive”, and that we should leave the process alone to achieve these beneficial ends. Contrary to this belief, it remains true that the outcomes of the evolutionary process cannot be predicted and any apparent benefits are just that – apparent. Laissez faire is not an appropriate way to get the best from the process if we wish to apply human value judgements to our world’s processes, whether climate change, the market or the pursuit of happiness.

Importantly the operation of cyclic systems in living processes, including the development and dissemination of ideas in individual minds and throughout the culture, are significant.

There are whole fields of study directed at complex systems and their interactions in the apparent chaos of our universe but an underlying process of the emergence of order from cyclic and non-cyclic systems of information appears to be present.


a Specialisation. While many of the emergent phenomena are complex and complexity can be seen as a significant component of evolutionary developments, it is important to recognise that complexity is not essential to the process. Specialisation may also be an effective way for a system to persist. Viruses, parasites and eyeless cave fish may appear to be retrograde organisms but are specialised survivors in particular environments.

b Multiplying involves the production of additional copies of the original and is a behaviour that emerged later in complex systems in the evolutionary process that includes the occurrence of life and consciousness. Identifying the precursors to life has been the subject of much study but perhaps it is the emergence of multiplication that is the critical preceding element. Iteration, copying (multiplication), replication (reproduction) are perhaps the critical steps in the chain of emerging evolutionary complexity.

c  Evolution is a much misused word. It originally meant something like “unfolding” or “incremental change” but has, in some usage, come to mean the same as Darwinian evolution. I am stepping away from the confusions surrounding that word by identifying cyclic system operation as incorporating the essential elements often meant by the use of the term “Darwinian evolution” and I am extending it to a wider scope by describing the emergence of adaptive change in cyclic systems.

d A cyclic universe may be more than a metaphor. It may be a harbinger of cyclic activity in our universe. Some consider that the universe may be the current iteration of a cyclic system that is fundamentally eternal. It is interesting that some suggest that the “strings” of the string theory of the origin of everything are manifest in two forms – closed strings and open ended strings. Some suggest that a cyclic universe must “evolve” with an associated increase in complexity. This idea seems to move the moment when everything came from nothing, to an earlier point but that theory still leaves the origins of everything no less clear.

e Ideas are formed from the nerve impulses starting with stimulation of sensory nerve endings producing electrochemical changes which are then modified by other impulses through various synaptic connections. I call these discrete impulses “nemes” (nervous system equivalent of genes or memes). The outcome of such interactions leads to the formation of coherent items we call ideas (or concepts, thought etc.). In the central nervous system of animals, and especially in humans, these may be stored in the memory and manipulated in the cognitive processes to lead to the emergence of new ideas which I call premes (precursors of memes). These might delight the thinker and might be communicated to our society as memes (cultural equivalent of genes). It may be more than a metaphor to envisage nemes and memes as cyclic systems subject to the same formula of iteration, variation and persistence that permits “descent with modification”.


  1. Campbell, John (2014). Universal Darwinism: the path of knowledge. Amazon.
  2. Darwin, C. (1859) On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life.
  3. Dawkins, R. (1976) The Selfish Gene. Oxford.
  4. Dennett, D. (2010). The New Replicators. Encyclopedia of Evolution. (e-reference edition) Ed. Mark Pagel. Oxford University Press
  5. Kelley, DB. (2013). The Origin of Everything. Woodhollow.
  6. Pross, A. (2011) Toward a general theory of evolution: Extending Darwinian theory to inanimate matter. Journal of Systems Chemistry, 2:1  doi:10.1186/1759-2208-2-1
  7. Randall, L. in Brockman, J (2014) The Universe. Harper Collins.
  8. Ridley, M. (2015) Evolution of Everything . Harper Collins.
  9. Turok, N. in Brockman, J (2014) The Universe. Harper Collins.

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