Part One : An intro to Complexly Evolving Ensembles (CEE)
In The Five Principles of Organized Complexity, I define, for the very first time, a Complexly Evolving Ensemble (CEE) as a competitively constrained self-organizing scheme, simply because it expresses “mechanisms” for memory and intelligence through multiply-localized decision-making units (constituting a huge network that forms a distributed lattice). It can also be understood as a dynamical system because learning is a dynamic process. CEEs are made up of ensembles of knowledge spaces that are related to each other by the way a learning agent understands.
A CEE is an evolving organization whose decay of equi-distributed order formation on a prescribed level, is cyclic, while simultaneously obeying an evolutionary scaling equation for growth.
In short, a Complexly Evolving Ensemble harbors a special type of dynamic, representing a competitively constrained self-organizing scheme, enabling various parts of it to “choose” which knowledge states it visits, based on a history of which knowledge state has been visited.
A CEE is recognized as an ensemble whose different aspects/states are always in perfect harmonic relationship with each other, no matter the combination of aspects taken into consideration.
A Prescriptive knowledge space is also a functionally specific knowledge space distributed within a Complexly Evolving Ensemble. This knowledge space forms the basis for that ensembles generation of order, which can be modeled within the context of the search for the most efficient mechanisms responsible for transport, control, and regeneration within that space.
Part Two : Organized Complexity and Knowledge
According to the Five Principles of Organized Complexity, Knowledge is described as invariant, immobile, unchanging, static, un-interactive and fixed…click here to continue.
Part Three : My Five Principles of Organized Complexity
In the Five Principles of Organized Complexity, Principles are described as pristine ideations from which particular derivatives are extrapolated.
The Prescriptive Principle in a brief sense indicates irreducible specific functionalities, that are related to each other by very similar solutions concerning finding the most efficient trajectories needed for the transportation, control and regeneration of energy within a Complexly Evolving Ensembles possibility space.
The Prescriptive Principle implies a conjecture about the intrinsic “sameness” of certain functional knowledge spaces, and their special energy efficient pathways, that together prescribe a Motivic-Operator. The Principle prescribes how Complexly Evolving Ensembles are constructed through the search, location, and convergence of the invariant properties of these knowledge spaces into a single uniform representation. The process of convergence within a learning agent would equate to the process of learning.
The Poise Principle like the name implies, describes the historic and present potential readiness of evolving Motivic-Operators to become a Complexly Evolving Ensembles future.
The Poise Principle is a conjecture about how the prescriptive Motivic-Operator, formed by the Prescriptive Principle and its overtones, gets expressed as real energy in physical space. It is a statement of the dyadic relationship that is formed between the Prescriptive and Poise knowledge spaces.
The Sustenance Principle as the name implies, clearly informs of the viability of any evolving organization to reach maturity.
The Sustenance Principle states that the most enduring and achievable rate of real energy expression for a transformed Motivic-Operator within a physical space, is given by the natural number sync between the primitive dynamic inherent within the triadic coupling existing between the Prescriptive, Poise and Sustenance knowledge spaces.
The Growth Principle explores structural possibilities and limits that exist when any physically evolving ensemble attempts to attain sustainability, with sustainability implying that the primitive orbits defined by the Prescriptive and Poise Principles, are in harmonic synchronicity.
The Growth Principle asserts that in other for a Complexly Evolving Ensemble to grow in a sustainable manner (without turbulence), then growth must be a consequence of continued synchronicity and harmony, between primitive orbits defined in an ensembles` Prescriptive, Poise and Sustenance knowledge spaces.
The Organizing Principle is the fifth and final Principle. The Organizing Principle determines the spatial arrangement and temporal sequence of events that take place within any Complexly Evolving Ensemble as it moves through the developmental sequence of the other Principles. The overall organizational structure needed to perform a set of Sustaining and Growth functions, utilizing the least amount of energy, while simultaneously yielding maximum efficiency, evolves only as a by-product of the evolution of a Prescriptive function as it translates into the capability to carry out such a function. This is what I refer to as Organized Complexity. It is a different kind of simplicity driven by intelligence and mimicked by primitive energy efficient trajectories. It is the physical manifestation of the mnemonic behind Organized Complexity, 6 6 6.
The Organizing Principle states that every Prescriptive knowledge space must evolve its final structure as a Complexly Evolving Ensemble, while displaying its K-Pattern. An example of a K-Pattern for the infinite sequence that is the set of natural numbers, is the pattern in the distribution of Prime numbers, and its structure is gradually built from the translation of 6-units along 3 coordinate dimensions. 6 units along the X axis, 6 units along the Y axis, and 6 units along the Z axis. This yields a one-line matrix, 6 6 6. This finding will be very important when we delve into the Standard Model of Particle Physics.
The Organizing Principle states that in other for any evolution to be considered a Complexly Evolving Ensemble, it must evolve a K-Pattern. That is, such an emerging organization must start as a functional knowledge space, which then developmentally transforms itself into a Poise knowledge space after a preset amount of time. These 2 knowledge spaces must interact in a sustainable manner such that they grow. When this happens, we perceive a K-Pattern, and it is on the level of the K-Pattern that we as humans recognize emergence and Organized Complexity.
The K-Pattern, which is the signature of Organized Complexity, is also known as the Prime Signal.
In truth, the process by which a K-Pattern emerges from within a Complexly Evolving Ensemble is completely replaceable. This scale invariant pattern will emerge in any Complexly Evolving Ensemble, as long as two conditions are constantly being met. These conditions are:
1. That there are a very large number of interactions amongst learning agents per any given unit of space-time; and,
2. That there exists a regulative intelligence that rationalizes any essential resource (such as energy, time, space, number, function, information etc.) around which complexly evolving organization resonates. This creates the necessary constraining conditions governing the space within which the organization must evolve, and hence forces it to mimic the generalized form of the K-Pattern.
In summary, what I am suggesting is that a K-Pattern/Prime Signal will emerge in the long term, out of the dynamics of any initially unfamiliar set of interactions, if the underlying interaction lattice is discrete, and can be indexed over Prime numbers. These conditions allow the underlying developing structure to mimic the behavior of the natural numbers as expressed in my model
Part Four : A K-pattern/Prime Signal as the rationale behind Organized Complexity
According to the Five Principles of Organized Complexity, the 3D organization encoded within the distribution of Prime numbers, forms the template upon which Organized Complexity is erected throughout the Universe, simply because space-time emerged from this organization. Living matter is matter which resonates with the fundamental harmonic of this distribution, which reverberates according to the frequency of the number 6.
The Standard Model, Special Relativity and Riemann’s hypothesis :
Fundamental particles are really just field excitations or resonances with distinct spin characteristics. How are these spin characteristics all related? What role does the critical line in Riemann’s Hypothesis play with regards to these characteristics from high energy particle physics?…click here to continue.
Part Five : The nature of the Infinite Possibility Potential
According to The Five Principles of Organized Complexity, it is impossible to tell the absolute size of the Universe, simply because there is nothing external of it to compare it to. The Universe could be infinitely large, or infinitely small. Either way, we and the Universe itself wouldn’t know or care. It is paradoxes like these that we meet when we begin to think of the Infinite Possibility Potential, and the singularity of symmetry-asymmetry which has been called the big-bang. What banged?? What did its emergence look like?…click here to continue.