Talk:Process Compartment Model and XenoEngineering

XenoEngineer@groupKOS.com

can we work with this... ```<Book Index>

Chapter 1

Process Compartments as a Foundation for Ecological Control Theory

(last edited: May 23, 2006)

Introduction

Theory of process compartments

The new thesis

The three transforms work like this

System image

Bi-level emergence, mathematical and physical models

On the question of symmetry

Process Compartment Hypothesis (PCH)

Stability, the hidden illusion

The new mathematics, and the new science

Summary

Introduction 
In Prueitt (1995), a theory of process organization was proposed as foundation to a computationally grounded class of generic mechanisms, algorithms, and data encoding. This theory attempted to take into account the creation and annihilation of natural processes localized into coherent phenomena by the cooperative behavior of complex systems.  Its formal foundation lies in pure mathematics and in thermodynamics of “weakly” coupled oscillatory systems having strong internal regulation and relatively weak intersystem influences.  The initial application of this foundation was in quantum neurodynamics and in cognitive neuroscience (following the conferences hosted by Pribram 1992, 1993, 1995, 1995 and Pribram’s books 1971 and 1991.) 

A simplification of the foundation will occur as we introduce structural ontology (Adi and Prueitt 2004).  This simplification is linked to data encoding, using the key-less hash table [1], and to the real time formation of structured information about the process being modeled.  The simplification is motivated by a complex theory of natural process.  The new information science retains the simplicity of data encoding and algorithms; while being consistent with the familiar, but truly complex, private experience with one’s own awareness. The techniques and assertions of fields like artificial intelligence do not have this simplicity nor naturalness. 

The core assumption made, in the theory grounding structural ontology, is that regularity of natural patterns are caused in part by tendencies to ignore small differences.  Systems, perhaps even non-living systems, are involved in the emergence of function from substructure.  Function imposes certain equivalences during the formation of natural category.  It is the phenomenon that natural category emerges that motivates all of the theory and observations that follow.  We ask “how” natural category arises and we use our answers to encode, into data structure, structural information about emerging categories.  The encoding is localized as “n”-aries, as discussed in Appendix B. 

In a familiar instance, we observe the tendency to remember only part of experience and as we do this we often treat the particular as if a thing seen before.  The experience and previous experience are categorized together and seen as being the “same thing”.   An example would be a discriminatory behavior or preference for one type of food as opposed to another. 

A relationship between human mental imaging and action-perception cycles is implicated as being part of the mechanisms that create experiential category.  Some scholarship about this relationship is presented in order to help define intellectual background.  This background is needed to ground a human-centric use of machine ontology, sometimes called web-ontology [2].  The “n”-ary encoding is the first step in developing an alternative to W3C standards.  The core insight is that action in a reacting world leads to an observation about the consequences of changes made to a responding system and thus informs the responding system about itself via changes made and perceived in the system's environment.  Web-ontology has been ushered in by the Semantic Web movement and by the related academic field of artificial intelligence.  However, the origin of information design sets with a few self appointed “knowledge engineers” and not within normal everyday usage.  The “n”-ary alternative is used within action perception cycles, where part of the cycle is embedded in normal everyday usage. 

In the last part of the twentieth century and the first part of the twenty-first century government extensive and persistent funding of so called software agents lead to mistakes in the design of web ontology.  The mistake revolves around the notion that computer programs can be the same as natural intelligence.  The situation remains difficult to clarify. 

The theory and technology for “structural” machine ontology was developed in the years 2001 – 2004 and is presented in later chapters.  Between 2004 and 2006 we developed a working understanding of the semantic web information technology standards.  These standards are developed using collaborative processes by the W3C and OASIS organizations.  The standardization process itself is an example of the formation of natural category, and thus the causes of the specific standards lend insight into the formation of natural category.  In this case, the observation is made that W3C standards developed to help the information technology sector achieve business objectives, whereas the OASIS standards were more oriented to shifting the origin of control, in new information design, from the software vendor to social process.  [3]

How can the scientific literatures curb this business oriented conformational process by exposing when in nature one finds truly non-deterministic processes? 

In Prueitt’s 1995 – 1996 work, an analogy to human self image is used to communicate how natural compartmentalized processes act in a natural setting.  The analogy is broad enough to cover any natural system, ie a complex system in Rosen’s use of language [4].  Mathematics is a simple system when seen in isolation from its role as a communicative language of science.  An outline of some mathematical concepts was developed and expressed.  This outline is given below.  The formal concepts are related to the study of emergence and stratification of physical processes.  Over the past two decades, the outline was not filled out to the degree that it should have been.  However, the 1995-1996 work seems as valid in 2006 as it was in 1995.  To finish this work would seem to require changes in support structure so that the mistakes persisting in artificial intelligence and semantic web communities can be directly challenged.  Recent trends are hopeful and can depend on well established formalism and extensive scholarship. 

Mathematics, in Hilbert spaces [5], gives description to how compartments might be studied in the context of temporally registered energy distribution in separated spectral strata.  Mathematics in Hilbert spaces can be mapped to descriptions expressed as discrete formalism [6], giving us a rigorous transfer of correlation analysis to data encoding in the form of “n”-ary web ontology. 

We found others working on technology and descriptions that depend on an encoding of structural ontology into spectral strata.  By structural ontology we mean actual reality, not the abstraction that one finds in web ontology language (W3C standards).  We mean the structure of natural category observable via direct perception or even instrumental measurement such as with electromagnetic or optic devices. 

An analogy between spectra processing in the brain and computational process within structural ontology is to be established in later chapters to ground a text retrieval and knowledge management paradigm for distributed collaboration in web environments.  Chapter 10 is developed, in 2004, in collaboration with several colleagues to reveal the nature of the Adi structural ontology for natural language understanding, and the corresponding generalization of his development experience.  This generalization is a “generative methodology for creating structural ontology.” 

Appendix B expresses a notational system consistent with the above remarks. 

Theory of process compartments
Prueitt’s 1995 theory of process compartments described what might be necessary to the organization of experience.  First, it may be necessary that natural phenomenon self organize into strata, and that the phenomenon in each strata emerges through an aggregation of substrate phenomenon.  Natural category forms through a reification of functional invariances imposed during periods of emergence.  Human memory systems may be responsive to managing the aggregation process.  The real situation cannot be expected to be simple.  Complexity is defined as a property of real situations, particularly during the emergence of function [7]. Complexity as defined by Robert Rosen seems necessary.  A non-deterministic aspect to the emergence of function may be necessary if the exercise of choice occurs.  For us this is not a religious concept, but one developed from direct experience not only with our private observations about human choices by with underlying physical, and non-living, properties.  Non-deterministic phenomenon may always be present anytime an emergence of something is occurring.  We are reminded that many of the real mechanisms on which human choice depends are observed in non-living systems.  Living systems may be expected to take advantage of underlying physical phenomenon.  Part of the mechanisms involved is what we call “awareness”. 

A specific number of mechanisms are involved in the expression of attentional behavior, such as awareness.  In stratified theory, we represent these mechanisms as acting with elements of substructural memory resource.  The aggregations of substructural resources are also thought to be by environmental constraints.  The mutual entailments, the full set of causes, are thought to create meta-stable compartments experienced as mental events. 

These compartments are physical phenomenon and should be observable if one looks in a proper way.  However, scientific reductionism asserted that logical coherence must be used to express the full set of causes, and this just seems to not be the way the natural world is organized.  Again, the notion of coherence can be understood as something that is build up from phase coherence seen in electromagnetic fields.  To expect that all “fields” must be forced into a single coherence may be logically satisfying to some, but the impact that such an imposition would have, if this were possible, would be an annihilation of everything.  We do not see this annihilation phenomenon in astrophysics.  What we see is both coherence and shifts between complex systems while coherence is challenged and systems undergo change. 

The contents of experience, however, may not be directly observable except by the person him or her self who is “experiencing” awareness.  In stratified theory, the compartment is seen as a physical phenomenon with stability far from thermodynamic equilibrium.  The compartment’s stability depends on the substrate as well as the environment.  Simply stated, the compartment emerges from a substructure and is constrained in its form and function by a set of laws imposed as environmental influences. These environmental influences include constraints imposed by neurophysiology. Underlying the stability is phase coherence [8]

Using notational language about the structural ontology of process compartments, the relationship between mental imaging and action-perception cycles is modeled as including a set of generic mechanisms.  We then use analogy to develop the stratified web ontology first proposed by Prueitt in 1999 [9]. 

One conjectures, that in biological systems, these mechanisms are available to an intentional system behaving within ecology.  Based on an extension of Soviet-era cybernetic, we developed the specific set of structure-to-function relationships, involved in a specific phenomenon.  We will see in later chapters the development of a “generative methodology” designed to create a model of the cross scale mechanisms that are involved in the emergence of compartments of various types.  The generative methodology uses formalism that describes these generic mechanisms.  Again, the key concept is that during emergence the needs of the environment shape the potential that develops due to the aggregation of substrate.  One sees this phenomenon in physical chemistry, when molecules form and expression functional properties.  In organic chemistry, the cross scale expression is often far most complex.  An example is gene and cell signal pathways expression [10].

We conjecture that the emergence of any type of physical phenomenon can be modeled in complex situations, specifically in the situations involved in the formation of mental event.  We argue, philosophically, that the regularity of any of these naturally occurring mechanisms is reinforced due to minimal energy and effort constraints that must apply to any living system competing for survival. We mean by this that the living system develops a perceptual system that relies on as much regularity in response requirements as possible.  From this argument we have developed an approach towards deploying computer based ontology with three layers of abstraction.  The result is structural ontology having a simple data encoding.  The data encoding is so much simpler that W3C web ontology language standards that the eventual adoption of these encoding methods is seen problematic to the current information technology industries.  Adoption barriers exist for this reason.

To understand structural ontology we need description and motivation for generative methodology.  A generative methodology is used to develop structural ontology through an iterative process.  The motivation for generative methodology comes from a number of origins.  Most of the material in this book is designed to reveal these origins.  In 2006 an OASIS standard [11] was adopted that specifies examples of computer mediated development of web ontology templates, and the necessity for periodically involving human decision-making.  The primary concept being introduced into information technology standards by the OASIS organization is that choice points must be identified through a process of human decision making, and that resulting computer based web ontology is then usable as part of an automated production of multiple possible outcomes.  The natural emergence of category is finding an expression using information production standards.   The OASIS standards places community based resources in the hands of those who seek to shift the origin of the design of social information from the few to the many. 

Starting in 1991, on obtaining a research position at Georgetown University [12], we reached into several disciplines in order to ground the generative methodology.  Ecological psychology, founded through the work by J. J. Gibson in the 1950s and 1960, was a good place to start.  Ecological control theory emerges from an understanding of the generic principles involved in the relationship between action and perception.  To be sure, the concept of Darwinian evolution is modified to include mechanisms that produce replication of functional responses to perception and provide regularity in the acting and behaving of living systems.  It is these replicated functional responses that we look for in applying the generative methodology.   Prueitt’s efforts, 1985 – 1988, on theoretical immunology and on formal models of biological neural networks were also instrumental in the formulation of generative methodology. 

According to theory developed within the ecological psychology academic community, action-perception cycles generate compartments out of a system image in the presence of external stimuli.  For Prueitt, compartments always meant organizational stratification.  Stratified theory defines "system image" as a reflection of temporal non-locality realized in a field manifold and having meta-stable potential localities (attractor regions), and ecological affordance (Kugler et al, 1990).   The system image is thought to encode into some part of its mechanisms information about these attractor regions.  How this is done was one of the open questions. 

The notion of a substructure, from which material is aggregated, is essential to how we formulate the theory behind the generative methodology.  It is the entanglement of the consequences of those elements of substructure that are present locally that forms a key part of what 

Claude Sonnet 4.5 Desktops

One

Looking at Prueitt's process compartment theory - the implementable elements are:

• • Key-less hash table for structural ontology encoding** - This maps to your clsMatrix append-only binning system. The text describes aggregating substrate elements through functional equivalence classes.

• • "n"-ary encoding referenced in Appendix B** - Need to see that appendix, but likely relates to your UPT 4-point stereoscopic method for consciousness pattern detection.

• • Spectral strata correlation → discrete formalism** - This is your Markovian Integrals time-series work. The text describes "temporally registered energy distribution in separated spectral strata" which maps directly to your multi-stream synchrony detection.

• • What's executable:**

1. **Process compartment detection class** - VB6 class implementing the stability analysis for meta-stable compartments through phase coherence measures across temporal strata

2. **Structural ontology encoder** - Takes perception-action cycle data and bins into equivalence classes using key-less hash, tracking emergence through aggregation

3. **Generative methodology engine** - Iterative refinement system that identifies choice points where human decision-making must override automation

• • What's missing for code:**

- Appendix B notation system - Specific mathematical transforms mentioned ("The three transforms") - Concrete phase coherence calculation methods

Do you want the VB6 process compartment class implementing the emergence-from-substructure pattern with your existing clsMatrix infrastructure, or is there a different Prueitt formalism you need instantiated?