Anticipatory Technology with Fractal Logical Entailments
Paul S Prueitt, PhD
Thursday, December 20, 2007
Introduction
This outline is a first effort to
integrate the threads of basic research developed independently by a number of
scholars. Several schools of thought
are to be integrated. I wish to
acknowledge the origin of informal collaboration, and to use attribution. My wish is to empower a deeper scientific
discussion than would other wise be allowed.
However some attributions are not possible. The communities involved are
diverse and scattered, often working independently and without knowledge of the
others. There does seem to be a new
school of thought arising about how computing and human communication will be
coupled.
The work proposes to develop some
formal models, using elements of stochastic theory and an encoding process into
n-ary web ontology language [1]. For example, Laskey et all propose a
straight forward extension of the OWL [2]
standard that encodes probability patterns, for Bayesian analysis or perhaps
other kinds of stochastic knowledge constructions. This n-ary ontology language is called PR-OWL, with the “PR”
standing for probability. My work could
build from the PR-OWL constructions, while adding the elements of tri-level architecture
and quasi axiomatic theory, also called topological logics. I discuss topological logics in chapter six
of my book “Foundations”. [3] Laskey’s work has some similarity to several
potential software designs, several of which I have studied.
I wish to define an economic vehicle
that if used might allow the expression of a fractal entailment [4]
for anticipatory technology. [5] This expression has great economic
potential. It may be predicted that
markets will eventually exploit this potential, for reasons that we wish to
make clear. There are two approaches to
making this clear. The first is in
philosophical arguments. The second is
in building an actual computer based distributed platform where mechanisms for
a new economy are in place.
As discussed below, nature appears to
organize around self-organization within organizational levels. In particular, the machinery used by living
brains in creating an anticipation of real world experiences is discussed in my
1988 dissertation and in a short paper. [6]
These mechanisms have so far not been incorporated in artificial intelligence
systems because the mechanisms explicitly acknowledge a non-algorithmic aspect
to human consciousness (as discussed by Roger Penrose and others). [7]
We wish to make anticipation of real
world experiences common and without ownership. We propose that an integration effort should occur in a framework
that is not classified and which will be used by everyday people in the context
of consumer markets. Why? There are two
answers, one political and the other moral.
Without public awareness of the issues raised regarding collective
intelligence it is unlikely that certain constitutional rights and national
security issues can be reconciled.
Consistent with the design of the
“glass bead game” theory [8]
the governing body will be not public.
The reason has to do with attribution and the private effort required by
the founders to create the technology and procedures for bead game play. The bead game design has, since 1997, three
groups of players. The inner group is
composed of bead masters. These masters
must be known to each other and have agreements regarding collaboration and
intellectual property. The bead games
of the Masters will be recorded and then archived as examples for others to
study.
Our proposal is to follow a set of
protocols in our research deployment of an anticipatory technology. These protocols will be understood the world
over, due to the popularity of the book, "Majestic Ludi: The Glass Bead
Game". The protocol will lead into
agreements consistent with the BCNGroup Charter. [9]
A fractal logical framework is to be
created based on an integration of selected scholars’ works. This integration task is not so great a
task, when compared with the works already completed. The deployment of the framework is then an outcome of some small
amount of work to be completed soon.
Initially a specific group of individuals are invited to have membership
in the governing body. This body will
reflect the interests of scholars.
Specific objectives include the finding
of funding to run a think tank this summer (2008) for two weeks, either in Canada, EU or other location, and to
support preliminary work on Anticipatory Technology with Fractal Logical
Entailments. The author is looking for
a funded position for two years to pursue this work.
Game play
First we state the principle assertion
of the second school. It is essential to the second school intellectual
position that we assert, due to specific arguments that are made elsewhere,
that the individual human or living system is capable of awareness. We also assert that computer programs are
not.
Now, we may address the framework we
propose for bead game play. A
technology will be developed that rewards entities, when anticipated conceptual
formulation is judged by a fractal logical framework to be "in
play". To be in play, a new
composition will have a fractal linkage to previous beads expressed in similarity
measures.
A review of the BCNGroup bead game
design is helpful. [10]
Similar to how the wiki works today, an
evolving body of knowledge is to be developed by individuals who are acting
anonymous as members of a community.
The play of the game is to be orchestrated by the Magister Ludi,
consistent with the behavior expressed in the book by the literary author
Herman Hesse. The Magister Ludi is a
functional role with fictional characteristics revealed in Hesse’s novel.
We have prototyped the fractal
framework with digital music inputs.
This prototype is far simpler than a full bead game with linguistic
processors. The branding language
includes the phrase, “let the bead games begin with music”. The business plan includes the development
of 25 channels of satellite audio supporting real time orchestration of
individual creative musical expression.
The music d-GBG is, will be, a global jam session, experimenting with
the notion that real time expression is not the same as recorded digital
products. A Creative Commons license
will be created to terminate ownership of the output of the music d-GBG. Artists will be compensated with attribution
and with money proportional to the number of listeners. The technical details are held in common
between a group in Monterey California and the BCNGroup.
An essential element found in
contributing scholars’ works is that of the concept of stratification and
fractal expression. We both observe
that the expression of humans, social systems and other systems of living beings
involves more than what deterministic mechanics allows by itself. I have developed a software interface design
based on the encoding of human responses and class - subclass taxonomy, into a
logic system having a fractal entailment.
The underlying architecture for an
intelligent back plate is tri-level and anticipatory in nature. Neuro Linguistic Programming (NPL)
principles will be used only as a primer designed to teach about
self-limitation. NLP principles will be
deepened using Briggs-Meyers, and a number of other systems for archetyping the
individual. Deep linguistic theory
developed by Adi and Prueitt [11]
will be combined with a general framework theory [12]
to produce a knowledge operating system design to be used by a single human
user.
A back plate will be possible, using the
technology designs developed by Prueitt. [13] This concept involves the use of distributed
compression dictionaries and a linkage between compression and decompression
and the development of indexing based on, as discussed above, a logic system
with constructions similar to the PR-OWL language, equipped with Soviet era
topological logics and an inference engine based on the extended Mill’s logic
(Prueitt, Foundations, Chapter Six). A
measurement process will be used at several levels of organization. For example, the individual, the emerging
group, the stable group, etc has images of self that are layered and nested
within other systems. This work builds
on work by Prueitt and Stephenson (2005) [14]
and Prueitt (2004) [15].
How is this work to be understood
Anticipatory technology with fractal
logical entailments may not be so difficult to understand. Some conceptual imagery is possible.
Imagine a fractal encoding of a digital
picture. In this fractal encoding there
is, in fact, an inference (or entailment) mechanism. The fractal is a small matrix that is used to process the color
and intensity of individual pixels in the digital image. In the decompression
of a fractal encoded digital image we may iterate beyond a certain point to
guess what is not seen in a digital image.
Knowledge might have a similar digital representation.
The fractal logical entailment is a
mechanism that processes linguistic input. Mapping this representation to
various knowledge frameworks will follow the work by Prueitt, Adi and Prueitt,
and by Prueitt and Stephenson.
In the digital image, the retrieval
mechanism is simply the iterative processing of the number of iterations
allowed in the decompression before the image is said to be complete. If the number of iterations is set higher,
then one may see into the new digital output additional detail that was not in
the original image. This is the
principle that is exploited by our work on fractal logical entailments.
One of the paradigmatic assertions of
the second school is that phenomenon expresses at various time scales in a
self-similar fashion. This means that
anticipation, including human intuitions, is built to be sensitive to these
patterns.
In summary: In our mutual theory we see
that a fractal entailment might actually underlay physical existence, and thus
be responsible for what we regard as our human sense making and inductive
capability. The principle is applied to the reification of ontological
structure composed of universals and stated as concepts, from the experience of
particulars by human beings. Of course,
the technique is not as simple as the use of fractal compression. In the digital image, the expression
mechanism is simply the iterative processing of the number of iterations
allowed in the decompression before the image is said to be complete. If the number of iterations is set higher,
then one may see into the new digital output additional detail that was not in
the original image. This is the
principle that is exploited by our work on fractal logical entailments. The
fractal logical entailment is a mechanism that processes linguistic input.
In the next section we address an area
of active application. This area has seen success in several important economic
sectors, in particular medical science.
Application of anticipatory technology in the automated
understanding of research literatures
The continuous pursuit of knowledge has
resulted in the classification and the development of a variety of specialized
disciplines of knowledge. These
pursuits benefit from the advancement of the analysis and understanding of
various causes. These causes include
what is often referred to as natural law, gravitational affects etc; but also
includes social causes and personal expressions of free will. By causes, we mean the full entailment of
phenomenon of any kind.
Collectively the results from human
pursuit of knowledge do form the sum of our perceived knowledge. This sum represents our collective attempt
to explain and further our discoveries.
There have always been issues of self-limitations related to the
advancement of science. These issues
are important to our proposed use of anticipatory technology. Automated and systemic processes are
attempting to synthesize the advances developed by scholarship. As this process matures, we are faced with
issues related to what might be called the “rational model.” The question arises about the possibility of
a “theory of everything”.
My research proposal [16]
discusses the phenomenon of coherence in the context of self-limitation and the
human need to act rationally within some viewpoint. We have asserted that the human sense of rational coherence and
viewpoint is part of human discovery.
This sense of rational coherence can be; however, the causes of barriers
to understanding two viewpoints, with separate cultural groundings, at the same
time. We assert that there is not and
cannot be a single viewpoint which is fully universal. This assertion is consistent with the
linguistic theory proposed by Benjamin Whorf [17].
Various technical challenges, in the
context of web ontology languages, are related to the issue of conceptual
coherence and rationality. These
challenges are seen as philosophical, and that perception is part of the
barrier we have found. The challenge is
real. Without addressing this challenge
the inclusion of probabilistic or stochastic models of knowledge, as in Laskely
et al, will not completely resolve the
knowledge acquisition nature. The
challenges are seen in failures to define well-specified web language for the
merge of taxonomy and description ontology.
The failures are also at the root of collective responses to
fundamentalism, and helpful in bringing social awareness to these roots. The technical support for shifting viewpoint
is seen, also, in everyday living.
In many current data management
systems, taxonomy and description ontology is used to organize textual
data. However, so organized, the data
does not fit within a fractal or anticipatory framework. Current data systems have limitations
because of fixed organizations and because there are no substructural
generative mechanisms. The most common
challenges are seen in failures to achieve reconciliation of cultural and personal
conflicts. The approach I am taking
re-defines these challenges and by-passes the merge and discovery concerns
framed by the W3C standards for description logics and RDF. The Topic Map paradigm is more fully used,
but in new ways. The back plate is to
be realized.
The issue of rationality has many
manifestations. However, perhaps
nowhere are the positive and negative aspects of rationality seen more in how
we manage our cultural knowledge. Human
discoveries address various sequences of past events and enable an anticipation
of future events. This occurs both
formally, and is expressed as mathematics, and informally. Up to now, mathematics has been used to
model only those events that are modeled in deterministic terms. For example some of the classifications for
these disciplines are engineering, chemistry, biology, economics, health
sciences. But there are also other
disciplines such as religion, politics and various beliefs and others,
including music and literature. All of
these classifications are organized into disciplines, each with a unique
viewpoint in which limitations are intuitively understood. Can all of these be modeled using
mathematics, as classically understood?
In the foundational work, in logic and in set theory, we find that this
possibility has some constraints.
The new science
We are creating automated frameworks
supporting our collective understanding of the complexities of 'total
knowledge'. An excellent example is the
key bio-informatics cell signal pathway and gene expression ontology. [18]
In making this effort we 'differentiate' and classify. Often, if not always, this differentiation
uses perspectives expressed with contextual nuance. A need for contextual nuance has always been critical, and will
be true in future automated synthesis of human knowledge.
Mechanisms need to be in place that
account for contextual phenomenon. Our
proposal will deploy such mechanisms.
We pursue a deeper understanding within
each respective field of specialized knowledge. This is an ontologically assisted extension of normal scholarly
activity. The knowledge we seek also
includes results from psychology and sociology studies. We seek a better comprehension of self, of
our self and the selves of others. In
particular we are interested in clear knowledge regarding the fundamentals of
human behavior. Again, we see
contextualization as an essential part of the experience of knowledge, and even
more so when we attempt to understand self.
The contextualization seems to need to shift as one moves from one focus
to another. By developing
contextualization mechanisms we hope to properly focus our integrated work on
mining emerging scholarship. The
purpose of this work is to accelerate our ability to express positive
collective activities.
The requirement for advanced methods
arises because the emergence of new thought requires a sorting of sub-thematic
structure into categories and context.
A discussion of NLP methods will be revealed in the context of a
criticism of the science up to this point.
Various techniques are proposed that
involve the further categorization and differentiating of self-similar
components and the evaluation of the extent of these component's causal
relationships and perceived impacts upon individual and group behavior. In the glass bead game terminology, these
components are the glass beads being put into play by the bead players. The bead game provides the social context to
the development and deployment of very advanced collaborative technology in the
presence of advanced knowledge management technology. These collaborative technologies are formative and agile and
create NLP like interfaces where individual action perception cycles provide
the formative energy. Thus the back
plate supports individual self directed discovery.
The development of individual knowledge
may proceed based on process models.
Models of this type are still subject to some high degree of
controversy, and are not used as much as one might see in the near future. How is science to be advanced, if it is to
advance beyond materialist roots? How
does one develop science about the natures of human cognition and
awareness? Agility is needed. Such an agile process model may be seen in
scholarship on topological logic. [19]
Other process models are being used in everyday enterprise management. I have some experience with all of these
models.
Some of the modeling processes
differentiate rather than integrate. Differentiation is required to further the
understanding of the relative importance and influence of the various
sub-components. The process of
differentiation is in fact a process that produces what I have called
“categorical abstraction”. The
formation of categorical abstraction [20]
then results in a substructural ORB (Ontological referential base). With ORB encoding we have a provably minimal
data encoding, and thus one more level of innovation and utility. Other properties of my key-less hash table
technology are available for use in the tri-level architecture having selective
attention and orientation mechanisms as discussed in my "Research
Proposal". When these mechanisms
are commonly available, the individual may feel empowered by the play of the
bead games.
It also has been long recognized by
sociologists that the decision making process, especially when done in a
climate of uncertainty, are not just products of rational judgment, but also
reflect heuristic shortcuts which are susceptible to individual biases. Our
group’s proposals follow classic work on the levels-of-organization hypothesis
and the epigenetic principle. [21]
Following Bertalanffy’s work, Prueitt’s
stratification theory argues against the concept of reducing higher levels of
complexity to lower levels. An interactive model developed within stratification
theory may best capture and describe decision-making process.
Comparison to other methods
Certain criticisms are made regarding
numerical models of concepts, and logical entailments seen popular in web
ontology languages and in the schools of artificial intelligence. This criticism suggests setting aside hard
forms of knowledge engineering with an alternative long advocated. The alternative is called the second
school. [22]
Our methodology has an inherent
potential to formulate and analyze logic-based problems and dilemmas, which
exist in real-life, in a more structured and complete fashion than other
existing methodologies. Most of these
methodologies are either number-based or heuristic in nature. Numerical and heuristic methods includes
most of the conventional engineering methods of artificial intelligence,
methods which are also used in sociology, physiological medical treatments,
inter-personnel and inter-social conflicts, etc. The methodology can address problems and issues to further
enhance the nature and scope of social-stratification dimensions (including
power, prestige and wealth), systematic treatment of group life, social
institutions, social problems, social change, and social control. This methodology should be revealed in a
game form, so that scholars might shine light on constitutional issues.
Therefore it is important to review and
compare the current state of the art modeling techniques, such as, Expert
Systems, Fuzzy Logic and others to illustrate the advancement of our
methodology over these and other existing state of the art of modeling
techniques that are generally numerically based, or are based on the limited
nature of description logics and ontology web language. In complex problems, the findings of various
disciplines can be categorized into tangible and intangible components and
events. This categorization may not in fact be completely reducible to
numerical models. Klaskey points this
out in his paper on n-ary representation of the structure of probabilistic
reasoning. The case is made that
concept-based methodology is essential to the kinds of Internet based
collective experiences we are envisioning.
Logical Proportional Analysis
Logical Proportional Analysis [23]
is a self-contained non-numerical process.
It is designed to interact with humans. The processes supporting
proportional analysis do mimic certain specific aspects of the human logical
thinking process. The analysis seeks to
identify and then measure occurrences of proportional rations between patterns
that are expressed at different time scales.
As such, proportional analysis generalizes the well know fractal
encoding and decoding of digital images.
The analysis fits over “raw” data that might be acquired from any real
time expression of any natural system, including an economic system or the
expression of a single human in text, or the expression of a group of
humans. Prueitt and Stephenson (2004) [24]
and unpublished papers by Prueitt suggest one class of applications. These applications are to the measurement
and analysis of patterns of cyber attacks, vulnerabilities and response
mechanisms. Evidence for fractal
composition of cyber security data is suggested in my private work with
Stephenson.
A number of mechanisms involved in the
biological response to stimulus have a computational model. These models are reviewed in Levine’s book. [25]
A specific approach to modeling biological mechanism is found in my 1988 PhD
thesis [26],
and is derived from the traditions of A. R. Luria [27]
and Karl Pribram [28]. The algorithmic implementations of these
mechanisms models these can be used to reify ontology web language based
universals from particulars seen in measurements. These aspects include interaction, as well as the mapping and
transformation of components and events in a causally entailed
relationship. The processes, proposed
in my “Research Paper”, are bounded in a way similar to the limitations of
human perception. They are also unlike
any other existing state of the art comprehensive modeling techniques, but have
some well specified historical roots in certain disciplines known in science
communities.
In proportional analysis the causal
characteristics of human categorization of knowledge of various disciplines is
integrated into a class - subclass hierarchical components and events. This
process was illustrated in many real world examples. What is different is both
the biological response mechanisms, as discussed above, and the fractal
analysis as expressed in a structured proportional analysis. The system is dynamic, and simple in its
algorithmic implementation, and thus the hierarchical structured formation of
events is an evolving causal transformation of the organization of data. These transformations can be used in many
ways. Specialists trained in specific
areas do not have to have a commitment to ontological structure determined by
knowledge engineers. The system can run
on real time data and can immediately produce topic maps about the observed
structure.
The transformation is a process that
involves multi-resolution lower level hierarchical entities and events. The simple underlying architecture allows
easy inspect of the formative processes involved in specifying thee entities
and events. The assumption of fractal
entailment supports a logical fusing process and formation of higher-level
entities of increasing complexities.
Human inspection of results in real time allows neural network type
reinforcement learning to occur.
Individual humans can comprehend logically based causal relationships
without necessarily knowing the detailed composition of the components
involved. This is due to a separation of structural forms and an ongoing
assignment of meaning via reinforcement learning mechanisms. A drill down into the layers is easy and
always possible. Only the knowledge of
structural relevance and of the causal interactions of sub-components is
required in order to know the structural forms.
The fundamentals of numerical modeling
and solution process involves a concept by the mind which is then transformed
into words and expressions, then into numbers, then a numerical solution is
obtained which is interpreted in words and then mentally realize and interpret
the numerical outcome. At each stage of the solution transformation processes,
there is a loss of 'something'. This
loss of something impacts the accuracy of the final solution outcome. One sees
a mention of this loss in the classical discussions by A. H. Whitehead about
the nature of induction. The ideal is
that ‘mind to mind’ translations exist.
However, the mechanisms underlying the computational support for this
kind of process should be simple, as the Orb technology is, and architected
using the stratified theory developed by myself. There should be no mystery as to how this translation is
achieved.
The suggested integration of
methodologies may be considered as a methodology; from mind to words to
word-string solutions. This is because
the human mind is seen as part of the loop.
There is an interpretation of words and then the mental realization of
the results. It is also an evolving
concept that is seen within the larger evolution of advances regarding our
understanding of human perception and knowledge.
Advantages and Relationship to other Existing Techniques
Cognition-related methods may be
confused with number-based techniques. Specifically those that may appear
similar pertaining to Artificial Intelligence; Fuzzy Logic, Genetic Algorithms,
Neural Networks and Expert Systems.
This section attempts to illustrate the key differences.
In Fuzzy Logic the user must quantify
the input parameter to obtain the corresponding values of the 'membership
function'. The processes of 'fuzification' and 'defuzification' are
number-based and are so programmed. Two users, with different 'perceptions'
would arrive at different conclusions in Fuzzy Logic, even if they both employ
the same membership functions. More realistically, two people with different
'expectations' may conclude that the
standard of living as "good" even
though their incomes widely
differ. The Union Rule Configuration
(URC) in fuzzy logic primarily eliminates the Combinatorial Rule (CR)
'explosion', however the process is numerically based.
Similarly Genetic Algorithms are
essentially combinatorial evaluation and optimization techniques. The user must
quantify the so-called 'fitness function', which measures the degree of fitness
(favoritism) of a given population. All processes of 'mutation', 'crossover',
etc. are essentially numerical assignments, which affect the formation of the
resulting 'genomes'. No margin is given for logical interpretation and
manipulation of the problem input and output entities
The Artificial Neural Network (ANN)
recognizes patterns and interrelationships in problem inputs. Defined outputs
result from past knowledge and experience obtained during the training of the
ANN on a number of training sets. Both formulation and processing of the ANN
technique are number-driven and the training is based on many input-output
scenarios. Neural Network techniques are number-driven and the training is
based on many input-output scenarios, all of which are pure numbers. In
contrast n-ary formation of stochastic patterns requires only definition of the
logical structure of the entity that perceives the inputs and decides on the
outputs. The patterns evolve to higher levels and eventually to a
generalization of the same problem, which may not have been originally
comprehended by the developer. However,
as the research proposal by Prueitt points out; ANN architectures are able to
provide to systems certain orientation features useful to living systems.
Expert Systems are tools in Artificial
Intelligence (AI) and have a relatively straightforward formulation, however,
some limitation on the type of problems that could be handled. The
'IF/THEN/ELSE 'clause structure of the 'Rules' is used to define pairs of
'Premises' and 'Conclusions'. The significant difference is that Expert Systems
are intrinsically passive, strictly rule-checking schemes, and can only reflect
what the 'user' knows (the contents of the 'knowledge-base'). Fractal pattern
analysis however deals with the user's dilemma as he/she perceives it, and not
as a mere 'pass'/'reject' verdict given to each rule in the solution process.
[1] Costa, Paulo C. G.; Laskey, Kathryn B.; and Laskey, Kenneth J.
(2005) PR-OWL: A Bayesian Framework for the
Semantic Web. Proceedings of the first workshop on Uncertainty Reasoning for the Semantic
Web (URSW 2005), held at the Fourth International Semantic Web Conference (ISWC 2005).
November 6-10, 2005, Gal:
[2] OWL standards for Ontology Web Language and is a standard of the W3C.
[3] Prueitt, Paul S (on web) “Foundation for Knowledge Science in the 21st Century” URL:
[4] Logical entailment is expressed as a fractal in Rimas Slavickas's work. A review of this work is to be made available to members of the governing body.
[5]Prueitt, Paul S (2005) Developing Anticipatory Responses from Thematic Analysis of Social Discourse http://www.ontologystream.com/beads/nationalDebate/challengeProblem.htm
[6] Prueitt, Paul S (unpublished - 2008) “A
Research Project on Mechanisms, known to be involved in learning”.
[7] Penrose,
Roger (1993) “Shadows of the Mind”
[8] Prueitt, Paul S acting as Founder of
the BCBGroup : URL:
http://www.bcngroup.org/site/beadgames/index.html see in particular
URL: http://www.ontologystream.com/area1/primarybeads/bead3.htm
[9] BCNGroup Charter: URL: http://www.bcngroup.org/site/aboutus.html
[10] Bead One is one of three foundational beads posted in around 1998. URL:
[11] Adi, Tom (2004) “The Adi Ontology, Part 1 – Part III”. URL:
http://www.bcngroup.org/beadgames/generativeMethodology/AdiStructuredOntology-PartI.htm
[12] Prueitt, Paul S. General Framework Theory is developed in a number of web pages and in unpublished documents.
[13] Prueitt, Paul S (2008). The Blank Slate Internet (Private document)
[14] Prueitt, Paul and Peter Stephenson. "Towards a Theory of Cyber Attack Mechanics." First IFIP 11.9 Digital Forensics Conference. Orlando, FL, 2005
[15] Prueitt, Paul S (2004) “Notational Foundation to Future Semantic Science”.
Unpublished except on the web at URL:
[16] Prueitt, Paul S (unpublished): “A Research Project on Mechanisms, known to be involved in learning”
[17] Whorf, Benjamin Lee [1933] (1975). The Phonetic Value of Certain Characters in Maya Writing. Millwood, N.Y.: Krauss Reprint.
[18] This project is detailed at www.biopax.org
[19] See references to works by Victor Finn in Prueitt, Paul S: Chapter Six, Foundations.
URL:
[20] Prueitt, Paul S (2007) A Research Proposal (private document)
[21] See also Bertalanffy, 1933; Schneirlia, 1957
[22] Second School web site: URL; www.secondschool.net
[23] Slavickas, Rimas
[24] Prueitt, Paul and Peter Stephenson. "Towards a Theory of Cyber Attack Mechanics." First IFIP 11.9 Digital Forensics Conference. Orlando, FL, 2005
[25] Levine, Daniel (1991). “Introduction to Neural and Cognitive Modeling” LEA.
[26] Prueitt, Paul S (1988). “Mathematical Models of Biological Mechanisms exhibiting Learning”. University of Texas at Arlington.
[27] Luria, A. R. (1973) “ The Working Brain”. Basic Books
[28] Pribram, K.H. (1971). Languages of the Brain, experimental
paradoxes and principles in neuropsychology. New York: Wadsworth.
Pribram, K. H.
(1991). Brain and Perception: Holonomy and Structure in Figural Processing.
Hillsdale, NJ: Lawrence Erlbaum Associates.
Pribram, K. (Ed). (1993).
Rethinking Neural Networks: Quantum Fields and Biological Data. Hillsdale, NJ,
ERA
Pribram, K. (Ed).
(1994). Origins: Brain & Self Organization . Hillsdale, NJ,
Pribram, K. &
King, J. (Eds) (1996). Learning as Self-Organization. Mahwah, NJ, ERA
Pribram, Karl (1993)
(Ed) Rethinking Neural Networks: Quantum Fields and Biological Data, Hillsdale,
NJ, LEA
Pribram,
Karl (1994) (Ed). Origins: Brain & Self Organization. Hillsdale, NJ, LEA