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THE VARIETY OF BEING:
IDEAS, CONCEPTS AND THEORY AND EXPERIMENTS
ANIL MITRA PHD, COPYRIGHT © MAY 2017
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PROLOGUE
This essay is a part [one of the paths] of the Journey in Being [Website.] For the complete story see the essay Journey in Being or the related Prologue to
a Journey in Being
The Variety of Being
… is a phase of Journey in Being. The focus is on, first, actual and hypothetical being and then on machine / computational simulation of being
For further details, see Journey in Being or the related Prologue to a Journey in Being
My Inspiration
My development has many influences and inspirations. Most of all perhaps are the influence of my mother who listened to my most absurd and
incomprehensible thoughts and my journeys in nature where I received so much inspirations in ideas and experienced so much contact with The Source
Journey in Being Website
http://www.horizons-2000.org
Anil Mitra
May 3, 2017
CONTENTS
OUTLINE
Prologue
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The Variety of Being
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Machine or Computational Intelligence - Introduction
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Applications
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Copyright
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Sources
TABLE OF CONTENTS
PROLOGUE
1
THE VARIETY OF BEING
1.1
Life
1.1.1
Human Being
1.1.2
Experience
1.1.3
Animal Being
1.1.4
Nature
1.1.5
Matter
1.2
Possible and Hypothetical
1.2.1
The Potential and the Possible
1.2.2
Sources
1.2.3
God / religion
1.2.4
LOGOS
1.3
Society
1.4
Technology
1.4.1
Tools and Machines
1.4.2
Technology
1.5
Theory of Machines
1.5.1
Finite, Discrete and Continuous State Machines
1.5.2
Functions
1.5.3
Fabrication
MACHINE OR COMPUTATIONAL INTELLIGENCE
INTRODUCTION
Origins
Objectives
Useful Features of Computation
2
MACHINE OR COMPUTATIONAL INTELLIGENCE
2.1
Analog vs. Symbolic Machines
2.1.1
Terminology
2.1.2
Agents
2.1.3
Computation
2.1.4
Computational Models of Mind / Cognitivism
2.2
Objectives: Machine Intelligence in Journey in Being
2.2.1
Understand and Construct Being / Mind
2.2.2
Assistants and Independent Tools in Research and Other Tasks
2.2.3
Design Principles
2.3
Theoretical and Conceptual Background
2.3.1
Ontology
2.3.2
Knowledge
2.4
Tools and Tasks
2.4.1
Tools
2.4.2
Tasks
2.5
Implementation of Objectives
2.5.1
Applications
2.5.2
Plan
LATEST REVISION AND COPYRIGHT
SOURCES
FOOTNOTES
THE VARIETY OF BEING
This essay is essentially the content of the section with the same name from Journey in Being. Although the content is currently close to identical, in the
future details will be assigned to the individual core documents while Journey in Being will be the primary document that binds the core
1
THE VARIETY OF BEING
This division is of intrinsic interest, contributes to knowledge and understanding of being, to transformation, value and realization in the Journey in Being…
and starts with being as we know it most intimately
1.1
Life
1.1.1
Human Being
For humankind, human being is, in an important way, the prototype of all being
I do not intend this to mean that human being is the ultimate substance and that the study of humankind should replace ontology or physics. I do not
mean that humans are at the apex of being, that humans are superior to other living being
Humankind has a material nature, a living and an animal nature. What sets humankind apart, for the purpose of study, is that the writer and readers of
these words are human. I sometimes wish I would integrate with my awareness, the consciousness of a variety non-human animals – from grand and
small. How wonderful it would be to integrate these consciousnesses with my own. However, it seems that there is a divide. Through communication, I
identify with other human beings in a way that that I do not – seem to – identify with other animals or plants. I am not sure how real that that divide is.
The empathy when I see a field mouse nervously dart around my camp and I remember my own fears, or the thrill when I see an a ntlered deer on a high
cliff against the setting sun – I wonder how true is the convention that my feelings are distinct in nature from those of the animal. For me, this casts doubt
on the distinctness of human and other kinds of experience. However, in the ways that human beings are unique – especially culture, learning and
technology, the kinds of experience are different. There, it seems, I must depend on my own experience and upon the narrative of other human beings.
And, in the ways in which human beings are not unique, I have, perhaps, the most direct awareness through being human; however, other living being
cannot be ignored
Thus, for humankind, human being is, in an important but not exclusive way, the prototype of all being
1.1.2
Experience
1.1.3
Animal Being
I should have been a pair of ragged claws
1
Scuttling across the floors of silent seas …
… an intrusion into logic and philosophy. He who sees where logic does not see, sees ragged claws are most present. We would think that human
adventure, and human intellect are the key… One might be a pair of eyes in the dark in a mountain cave rather than a fierce conquering brain
The animal is a foundation of human being
Beyond that, the presence of non-detached animal being, sometimes forgotten but not non-human… must be a way to all being
1.1.4
Nature
1.1.5
Matter
1.2
Possible and Hypothetical
1.2.1
The Potential and the Possible
1.2.2
Sources
Mythology and Religion
Literature and stories
There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy
2
Imagination and reason
Metaphysics
What is a Transformation of Being? [Section in Journey in Being]
The logic and philosophy of possibility and necessity
1.2.3
God / religion
The subject “God” although not dead, e.g. in Christian theology, is taboo in some circles and passé in others; it is something to be avoided. Here are some
possible reasons. The discussion focuses on general and academic sentiments c. 2000 in the English speaking world. The first is the idea of separation of
Church and State and its practical interpretation of the separation of religious and secular life; this is founded in the idea of freedom of religious practice
from politics but also in freedom from rational constraint. The actual social, political and academic scene is complex with a variety of emotions, reasons and
sentiments and, here, I do not want to undertake an analysis of the variety. However, as a result of the context there are circles where publicly subjecting
“God” to rational scrutiny is improper; and there circles where the very mention of God creates discomfort
On the other hand, God / religion is influential in politics everywhere in the world especially in America where politicians have to recognize large blocks of
Christian voters; and this influence has a significant effect upon the quality of life and freedoms of many. Whereas there is, in the United States, a
constitutional separation of Church and State, there is in fact a significant effect of the religion upon politics. The position, here, is not constitutional; were
it so, it would be pointed out that, in the United States, the First Amendment, guarantees both freedom of religious practice and of speech. Rather, I hold
that despite the common respect that is due to issues of faith, the influence of faith upon common life opens it up to public discussion
I cannot avoid mentioning academic fashion and norms; these are powerful institutions and to break the norms is to risk ruining one’s reputation. However,
even the fashion is loosely based in substance – even if there is no solid basis. The concept or idea of God inherited from religion – supreme being, creator
of the universe… – runs counter to the prevailing scientific and analytic spirit. There has developed a tradition that there is no room in this spirit or world
view for religious sentiment. The concept of God inherited from religion is so invested, on the one hand with institution, sentiment and tradition and, on the
other with Scholastic Philosophy as to make the neutral and piecewise discussion favored in analytic circles difficult
However, the study of being, of the real requires consideration of all being. That which we have not seen, and that which we do not know clearly cannot be
studied by empirical means alone; a concept is required to be investigated rationally and held in open view without prejudice. Many general concepts of
thought have evolved especially those of matter, being, and mind – there is no reason based in analysis to adhere to a concept as received. Further, the
foregoing inherited idea was from Christianity; ideas from other cultures or religions are much more capable of rational or analytic treatment. Such topics
cannot be adequately discussed without a field of concepts; and that entails system. Further, while science and analysis chart large territories of our world,
the arguments of this essay show those territories to be a fragment of the universe [this observation is not new or unobvious.] The metaphysics of this
essay is or includes a language, significantly by abstraction, for description of the vast areas not accessed so far by science and reason – or by religion. As
for the fact that the idea of God is significant to and cherished by so many believers, I believe that that is good reason to take up the idea of God and
subject it to the scrutiny of reason, to find what place there may be for it – in evolved or transformed form – in the universal metaphysics which may well
show what transformation of the idea may be necessary for realism
Does God exist? Is there – or will there be, or has there been – an actual being corresponding to the concept of God; or may God exist in our phase-epoch
of the universe? The latter question regarding the possibility of God arises due to the indeterminacy of process – evolution. The restriction to an phaseepoch of the universe is because in the one universe, without restriction, what is not simply a contradiction is possible and what is possible is necessary.
The real questions concern the nature of God and the concepts of God; this approach allows for a “conversation” between ideas, tradition and reality. The
question of the existence of God is one of the possibilities of being and our place within and relationship to those possibilities
What is the meaning of “God” in the context of use. There is no one such meaning; however, one use is in reference to the highest potential of being. Is
there an actual referent corresponding to this use? Just as the concepts of natural philosophy are allowed to evolve so should the concepts of theology
One approach is as follows. Think of the relation of the individual to the one universe. From the Principle of Being [Section in Journey in Being,] the
individual is the universe; this is ultimately true though not immediately within experience. This is a principle of the Vedanta i.e. Atman = Brahman or Self
= Ultimate Being. God, as being, is part of the one universe and, the interpretation of the idea of God from the traditions is that of a being that is
intermediate between the individual and Brahman, the universe. From the ultimate perspective there is good and evil but these are neither sought nor
avoided. From the immediate human perspective, immediate good and evil are moral issues but there are also occasions to take a neutral attitude toward
good and evil. The ultimate and individual meanings are related but not identical. At the ultimate level good and evil are forces e.g. of creation and
destruction and morality is applicable only in so far as there is an agency involved. For the human individual they relate to human values. Actions and
outcomes are right, good and so on; the terms are not properly applied to individuals. The foregoing defines a field within which the great variation in
traditions and theologies find interpretation and placement. The purpose of this paragraph has been to show a direction of understanding from the
perspective developed in the present essay [Journey in Being] but not to elaborate the reality, the symbols or the human psychology
I take it up as a sign to future evolution – without final commitment to preservation or rejection of the idea
… as the potential of being
… as ultimate Being: the ultimate in all beings
…as the creative principle from nothingness… none other than LOGOS [Section in Journey in Being]
In surveying religion, it is possible to be turned away by the arrest. Traditional religion holds to the past – for which liberal religion substitutes denial,
agnosticism, atheism and, in modern times, activism
Much of religion, especially of the texts and rituals, even where meaningful to adherents i.e. locally meaningful, is of accidental origin – does not furnish
universal or “large” ideas worthy of consideration as metaphysics, as part of the entire human tradition. There is however a core of significant ideas and
oppositions. These include the ultimate – God, origins vs. eternal being or return, human ethics and meaning and their relations to the total cosmos, the
nature of death and the destiny of the individual, continuation of the chain of being beyond the visible world…
1.2.4
LOGOS
LOGOS,
simply, is the concept of the possible. This simple formulation hides the infinite complexity of the idea; the universe – our phase-epoch of it – is only
a small phase of the possible. LOGOS may be referred to as the world of the possible but this is metaphorical even though the LOGOS “world” is sometimes
thought to be an actual but distinct world and sometimes thought to be an actual part of this world. LOGOS is, however, contained in the womb of
nothingness
The sum of all forms
The form of form
Second and higher order form
We saw that symmetry or form is required for more than transient existence
LOGOS
includes chaos and randomness
Does LOGOS exist? In view of the discussion of existence – from Journey in Being, LOGOS exists. Is LOGOS part of the real? In view of the same discussion
LOGOS may be considered to be real
1
T.S. Elliot
2
William Shakespeare
1.3
Society
1.4
Technology
1.4.1
Tools and Machines
Tools extend function for an individual or society and are discovered in play / observation of cause-effect in play
Here, play is not divorced from actual living but requires only that actions are not governed by necessity. Thus, in addition to design, adaptation [coevolution] is also involved in the development of tools [and machines and technology] whose origins are beyond the pale of history
Therefore, understanding and application [action] occur in interaction and there is no essential separation of hierarchy of understanding and action, i.e. of
techniques and the use of tools. These comments are an example of the observations in Justification and Action [Section in Journey in Being] and related
sections and apply also to machines and technology
Machines are tools that have a degree of independent function. For example, the driver handles a car with respect to starting, accelerating, steering,
breaking and stopping; however, much of the functioning “under the hood” while under the general control of the driver functions independently of the
driver’s input and without regard to the driver’s knowledge
1.4.2
Technology
Technology is the system of deployment of the world to ends; or
Technology is the entire system of knowledge, technique, production, delivery and use of tools and machines in interaction with individuals in the
deployment of the world to the ends of individuals and society; the interaction occurs in varying degrees of independence of the mechanical or machine
elements, from extension to assistance to independent function. By design, the independence is usually not complete although it may be significant e.g. a
robot that, after design and input, functions without further input throughout the performance of its function. In evolution, the degree of independence is
not under complete control of the designer and builder of machines and technologies; consider, however, self-designing machines
The phrase “deployment of the world” is important and is preferred over “deployment of the environment” since the world includes individuals, technology
itself and knowledge. Thus technology includes the interface between individual and machine, production systems, machine or computational intelligence
and the design of such systems
1.5
Theory of Machines
Electromechanical, and electronic; thermal and chemical; biological…
1.5.1
Finite, Discrete and Continuous State Machines
1.5.2
Functions
Simulation
Tasks: fabrication, transportation…
1.5.3
Fabrication
MACHINE OR COMPUTATIONAL INTELLIGENCE
INTRODUCTION
From this point to the end of this section on the Variety of Being, the content is that of Computers Beings Minds
Details for the origins and objectives are in Objectives
Origins
My interest in machine intelligence has two broad, interactive sources, machines as objects and as tools:
In understanding mind and being
Use, application
Objectives
This document is a specification and design of related uses of intelligent machines [machine intelligence] in Journey in Being
Useful Features of Computation
Memory and storage capacity
Processing speed
Sending / receiving information; communication, Internet
Automation, visual interface
Programmability for mundane and intelligent task
Document production, maintenance
2
MACHINE OR COMPUTATIONAL INTELLIGENCE
A machine does not intrinsically model anything
…except in the senses not used at this point that everything models itself and, if adapted and everything in the universe is adapted in some way in so far
as there are co-origins, models the world sufficiently well. One important point to note is that if there is modeling it is, generally, of the world which
includes the machine itself and the designer and builder…
However, a machine that assists in function or functions through having, copying or simulating understanding or function [adaptation] models or partakes
of a model and is an intelligent machine
2.1
Analog vs. Symbolic Machines
An intelligent machine that functions by having, copying or simulating structure, functioning or adaptation is analog, while one that codes the symbols of
understanding is also symbolic. A typical digital machine is symbolic – its states are combinations of binary [e.g. 0, 1] states and symbols are assigned
combinations that can vary according to application [program.] A typical analog machine models neural structure and, by analogy, is connectionist or
associative
Roughly, the operation of a symbolic machine corresponds to formal understanding as discussed in the division on Metaphysics or Knowledge and Action
[Section in Journey in Being] and operation of an analog machine corresponds to the Kantian intuition… and, as was seen in the earlier division, formal and
intuitive understanding are identical at root
Symbolic machines are not associative in any direct way and vice versa but according to the Church-Turing Thesis all sufficiently powerful computational
devices [with sufficient memory] are universal, i.e. any machine can emulate any other3
2.1.1
Terminology
The analog / symbolic distinction also has the following characterizations
Algorithmic computation / signal processing
Classical artificial intelligence / connectionism
AI modeling / neural net modeling
The analog approach is more “bottom-up” and based on a neurobiological metaphor i.e. what are thought to be key properties determining firing of
neurons are built in. The symbolic approach is more “top-down” and relies on the science and mathematics of computation
2.1.2
Agents
An agent4 is understood as:
Perceiving the world [which is the environment and the agent]; perception is thought of as seeking / receiving information about or representation of the
environment
Judging; judging is a composite and dynamic activity of processing information to decide actions achieve desirable outcomes; mechanization of judgment
includes computation and therefore agency includes computation
The activity is dynamic: in that complete processing of all information is not always possible or necessary or done before acting; what is desirable is
contextual and revisable; the processes toward outcomes may be explicitly incremental; processes toward outcomes may be dynamically incremental
in that information available before achievement of an outcome may be used to modify decisions regarding actions and what are desirable outcomes
The concept of desirable outcome has the following distinctions: positive outcome sought / negative outcome avoided; intrinsically desirable / rational.
An intrinsically desirable outcome would correspond to emotions or drives and for machines they might be “hardwired;” that a goal be associated with
a drive or that its satisfaction be hardwired does not make it imperative, for exclusive goals may enter into some kind of competition such as
“weighting” or be part of an intrinsic / rational hierarchy. Rational outcomes are explicitly chosen according to some criteria of success including the
satisfaction of intrinsic outcomes
Action upon the world
An agent has been defined as rational to the extent that its actions can be expected to achieve its goals or desirable outcomes, from the data given by its
perceptual processes. Assuming that an agent might desire [or that the designer, if there is one, might aspire to rational design] to be rational a number of
problems arise: there is no a priori reason to suppose that a mechanical agent with fixed goals is a model of being, mind or intelligence or that such an
agent will yield the most useful practical devices; there is no a priori guarantee that, even given an infinite amount of time, an agent can determine
appropriate actions and this is compounded by the fact that agents in dynamic worlds must operate in real time. In practice, “successful” agents need only
be sufficiently successful; where success is context dependent. [Note that the idea of optimality was not even introduced since the concept has significance
only in environments that are very simple or definite criteria can be successfully imposed; in such cases the use of single or multiple criteria of optimality
may be useful.] Two ontological problems with the concept of rational agency may be identified: the sharp division of activity into perception, judgment
and action; and the concept of a being as defined by an interest in goals or desirable outcomes, especially specifiable ones. Nonetheless, the idea of agent
as involved in its input-output is an advance over the classical artificial intelligence idea of machine intelligence as performance of isolated reasoning tasks
Any such judgment is value laden for reasoning tasks are useful; the values in question, then, include:
3
There is an issue of whether semantics is realized in computation. In proof theory, within limits, the semantic relations between propositions are
isomorphic to syntactic relations between sentences; thus if the syntax is intrinsic so is semantic
I have referred to the article Computation by Brian Cantwell Smith in the MIT Encyclopedia of the Cognitive Sciences, 2 nd edition, 1999, Robert A. Wilson
and Frank C. Keil, eds. However, in the present essay, there are a number of differences in treatment and emphasis
4
From the point of view of utility: having intelligent machines that operate more or less independently of designers and operators
From the point of view of embedding in the world; having intelligent machines that are less flat from the point of view of organization and so, at the
lower levels of organization, tied into the world
And so having machines that approach having mind / being in the senses that animals and humans have mind and being
2.1.3
Computation
So far the concept of computation has received some implicit specification. In order to better perform the following tasks it will be useful to define or
specify what is computation
Use the concept of machine intelligence in understanding being / mind
This becomes restrictive on the conjunction of two conditions: first, cognitivism, the idea that the brain is a computer i.e. that at an abstract level the
mind is a computer; and, second, on some conceptual or theoretical account of the nature / concept of computation
Developing and simulating machine intelligence for the following purposes: to advance the use and capabilities of machine intelligence; to develop
specific applications for use in the projects of the Journey in Being – these are specified in Objectives and include the understanding of being / mind by
developing models
In order to develop the concept of computation the following will be useful
Discuss existing concepts of computation, their rationale. Analyze these concepts, understanding how [if] they mesh and what they have in common
Keep in mind that machine intelligence falls under the topic of machines which in turn falls under technology
Remember that the concept of agent is not an alternative to the classical concept of machine intelligence as performance of isolated reasoning tasks but
incorporates the classical function into a more independent, “self-sufficient” concept. This independence is not a complete independence – individual
beings have degrees of independence and interdependence; in order to take steps to machine being and steps toward more capable intelligent machines
it will be useful to examine the kinds and degrees of independence and structure of organisms and individuals. Since the goal of intelligent machine as
independent agent / being is only one goal and the use of machines remains important, the performance of tasks remains important
Following are some existing concepts of computation as used in cognitive / computer science c. 2000 5:
Formal symbol manipulation – here, a symbol is a token for anything that could be a mental content or information such as a concept, representation or
word; a symbol is formal to the extent that it is independent of meaning but that the system of symbols belong to a grammar; and there is manipulation
to the extent that computation involves a transformation [in time] of the syntactic structures stored in computer memory. Independence from meaning is
independence from semantic properties such as reference or truth; the meaning is assigned by the builder / programmer / user
Computation theory based on Alan Turing’s construction of the Turing machine and the related Church-Turing Thesis, above, that all machines [with
appropriate conditions] can emulate every machine and so [1] the Church-Turing Thesis is not architecturally limited and, [2] the cognitivist [hypo-]
thesis that the mind is a digital computer. The idea of a concept / theory driven notion of computation is [has been] exciting because of the universality
of computation [on the Turing notion] and, since – the argument goes – the brain appears to be a machine, the applicability of any theory that may be
computed including formal logic and computability theory; the argument breaks down if brain processes are indeterministic which they must be
The concept of computation as the process of digital state machines which except for continuity appear to be equivalent to the Turing conception of a
computing machine. Infinite state Turing machines including continuous machines can compute [solve] problems unsolvable by finite state machines.
However, the concept of a digital state machine is interesting and useful since modern computers are [almost always] digital state machines
Information processing: that comes in semantic, syntactic and practical [Internet…] versions
Classic symbolic architectures: serial, fixed, symbolic, explicit, discrete, high level representations, exemplified by axiomatic inference systems6
Connectionist architectures: see comments above, in Analog vs. Symbolic Machines
Practical computation and architecture : the actual projects, commercial, research and theoretical that have driven developments in technology including
the consumer technologies and conceptual including AI and quantum computing. Most actual projects are implemented in high-level programming
languages such as C++, Java, Fortran. The interaction between this technological richness and cognitive science is rather loose and the future is rather
open and unpredictable
The theory driven approach is useful in that theories provide impetus to direction and coherence; as far as theories are reductions the reducibility must be
remain in interaction with more basic theories [logic, computability...,] and with actual developments. Actual development will be an amalgam of theory
[concept] driven ideas and actual systems – both academic and research on the one hand and commercial and application oriented on the other hand.
Actual developments vary from the theory driven, to practical architecture driven, to the deployment of developed software to theoretical and utilitarian
ends
One approach to the nature of computation is as follows
List and describe actual physical architectures; generalize to a system of possible architectures
List and describe actual interpretation based and interpretation free implementations of “mental” function; generalize, using the theory of mental
function that includes attitude and action as functions, to a system of possible implementations
Quantum-computation holds the following potential: due to the nature of quantum states, ability to solve otherwise intractable proble ms [by infinite orders
of magnitude;] massively parallel architecture; miniaturization; due to its physical basis, more faithful modeling of brain processing. The following questions
are raised: to what extent is the brain a “quantum-computer,” and, to the extent that it is, what is the contribution of the essentially quantum phenomena
such as indeterminism and the indefiniteness [or, rather, multiple-definiteness] of quantum states, what is the contribution of the power of quantum
computation and what is the contribution of the number of neurons and the massively parallel and connected but classical [non-quantum] structure of the
brain
2.1.4
Computational Models of Mind / Cognitivism
From the Church-Turing Thesis the following hypothesis seemed to be a small though exciting leap: human cognition could be emulated by computers
A variety of views have been held
Cognitivism: the brain is a digital computer. On account of the thesis of cognitivism there is, in cognitivism, a parallel between models of mind and
concepts or models of computation
Strong Artificial Intelligence: the mind is a computer program
Weak Artificial Intelligence: the operations of the brain can be simulated on a digital computer
These views have been criticized e.g. John Searle, The Rediscovery of Mind, 1992. Searle held that Weak Artificial Intelligence is trivial and argued against
Cognitivism and Strong Artificial Intelligence on the ground that digital computation is syntactic, it is symbol manipulation which is assigned but not intrinsic
to the physics. It follows that digital computers, in so far as they are digital computers but not on account of their intrinsic physics, do not have minds and
are not conscious, i.e. on the classical or non-quantum account the human mind functions as a digital computer but that is not the source of human
consciousness
The view, here, is that a computer can be interpreted as a symbol manipulating system but also, especially on the connectionist model, as a physical
machine. Or, a posteriori interpretations are at least as significant as a priori ones. Insofar as a computer manipulates symbols, reference, intensionality,
meaning, truth are assigned; therefore, as a physical object, without further physical properties, the assignment of semantic properties makes for mind not
significantly more than the minimal [if any] mental qualities possessed by a rock. Here, talk of mind refers to high-level mind and not to the mental
properties, whatever they may be, possessed by matter merely in virtue of being matter. Therefore, associative machines, on account of their physical
properties may come closer to being mental than do serial machines. However, without further development such as low level integration and high level
interpretation, the mental properties of associative machines must be small
In so far as mind and consciousness in machines is concerned the symbolic view may yet have some promise; however the view of a computer as a coevolving machine with a posteriori interpretation holds more promise; probably, both the source and recognition of machine mind and consciousness will
occur by transference / empathy though Theory of Mind [the theory of how individuals recognize mind – the empathy module of the brain – in other
entities] may also have a contribution
Additionally, there are implications of the introduction of the concept of agent in or as defining machine intelligence. Note that the idea of agent
corresponds to the inclusion of action as an aspect of mind – and to the fact that mind is embodied
2.2
Objectives: Machine Intelligence in Journey in Being
This document is a specification and design of related uses of intelligent machines [machine intelligence] in Journey in Being:
2.2.1
Understand and Construct Being / Mind
Design, experiment and construction of a machine, likely an [intelligent] agent, to simulate or have being / mind contributes in a number of ways:
As an entity in the Journey itself; in the division Metaphysics or Knowledge and Action [Section in Journey in Being], the questions of possibility,
probability and value of transformations were considered. Computation and machine agency are regarded as one approach to magnifying the
probabilities of transformation. The full implementation is a future and ambitious project. However, even as a tool, there is some contribution to “being.”
As a data point: if human and animal intelligence / being is one data point, machine intelligence is an additional one
The design and construction requires understanding of being / mind. Use of the understanding in a design and experimental setting will contribute to the
understanding
Artificial life
2.2.2
Assistants and Independent Tools in Research and Other Tasks
Conceptual representation, understanding and research: as an example, I compared database representations of two formulations [one based in subjective
idealism and the other in materialism] of Evolution and Design to determine which topics were of fundamental importance. I have used standard software
to develop a number of minor applications e.g. to assist in determining the main topics of Journey in Being
Technical applications
Text and website production
Management
2.2.3
Design Principles
These design principles are for design / use of computation in the objectives, above
5
Computation by Brian Cantwell Smith in the MIT Encyclopedia of the Cognitive Sciences, 2nd edition, 1999, Robert A. Wilson and Frank C. Keil, eds.
6
Computation by Brian Cantwell Smith in the MIT Encyclopedia of the Cognitive Sciences, 2nd edition, 1999, Robert A. Wilson and Frank C. Keil, eds.
The first set of design principles for the use of machine intelligence in Journey in Being are stated as a set of oppositions. In the following each side of the
opposition has importance
Theory and actual objectives
Machine as assistive and independent tool
Use as tool leads to independent deployment
Reasoning tasks and machine as agent
Design and [co-]evolution
Assigned and intrinsic reference
Flat and or multi-leveled with regard to organization
Lowest levels designed or lowest level integral with nature
Human / machine interaction will include dynamic interaction; i.e. machines are designed but, additionally, may interact in co-evolution in which [1]
both human and machine may change and, [2] through design and selection [rational and evolutionary] change may occur by transference of
properties / characteristics. The dynamic loop is: model – performance – redesign – new model
Non-design effects
Experiment
Hardware and software
Software description assigned or interpreted
Digital and or connectionist architecture
Design
Formulate an integrated configuration of system/software tools
Use standard proprietary, shareware, and freeware tools; focus on integrated systems
Develop software / tools as needed. In the planning phase conceive a system
Although the goal is an emulation system: first focus on assist / tool modes; second focus emulation as model / tool; finally, substitute / partial
substitute
The following are also important
Foundation in mind / body and knowledge / being considerations of Metaphysics or Knowledge and Action [Section in Journey in Being]
Knowledge representation [concepts] dynamics and foundation in the earlier division
Integrating the digital and associative architectural models of cognition
In so far as machine mind and consciousness is concerned the symbolic view may yet have some promise; however the view of a computer as a coevolving machine with a posteriori interpretation holds more promise; probably, both the source and recognition of machine mind and consciousness will
occur by transference / empathy though Theory of Mind [the theory of how individuals recognize mind in other entities] may also have a contribution
On account of the parallel between mind and computation in cognitivism, computer architecture, outlined in detail in Computation, provides models of
mind i.e. of cognitive architecture. Roughly cognitive architectures come under two classes: serial or von Neumann and connectionist or associative
architectures. The main idea of the von Neumann architecture is for programs and data to be stored together i.e. from an abstract point of view, there is
no distinction between program and data. The idea of the multipurpose programmable machine is implicit in the idea of storing programs. The main units
of the von Neumann architecture are processing, memory, input and output. Cognitive architectures inspired by the von Neumann architecture of
computation begin with the early idea of the production system of Herbert Simon and Alan Newell; the first general model of a production system was
the General Problem Solver in which the “structures” represented are primarily resident, in principle, in the program. Input / output information
processing theory is another class of cognitive architectures derived from the von Neumann concept. In representational models, the structure that is
modeled is put in explicitly in the data rather than implicitly in the program. In associative architectures, processing is done by many sub-processors
operating at the same time – in parallel; these date back, at least, to Aristotle’s theory of memory and include the work of McCullough and Pitts in
building models of neural networks and Donald O. Hebb in explaining psychological phenomena from global neurophysiological models. Since the work of
McCullough and Pitts and of Hebb in the 1940s, various theoretical developments, see Cognitive Architecture 7, a variety of theoretical developments has
provided a foundation for and introduced tools for application of associative architectures. And, finally there is a variety of hybrid von Neumann /
associative architectures that combine the strengths of the two approaches – the ability of von Neumann architectures to match human level competence
and the ability of associative architectures to model the context specific and multi-tasking aspects of human intelligence. Finally, the fact that, in the
brain, there is no intrinsic distinction or separation of architectures and that high level architecture / processing is built from the low level points to a
limitation and opportunity for progress in the concepts of cognitive architectures
The von Neumann architecture inspired the concept of the programmable computer as a general purpose machine. The introduction of compilers that
translate a program written in a high level language that is not machine specific in to a machine specific low level program significantly enhanced the use
of the computer as a general purpose machine. Specifically, not only is it possible to program machine intelligence [as part of the performance of
agents,] it is also possible to model agent and environment, i.e. to model agents and there actions and performance
2.3
Theoretical and Conceptual Background
A significant degree of useful theory has been covered in the present and other divisions. Therefore, the following treatment will be brief; it will primarily
make reference to the locations of the developments. The primary locations are the discussions of knowledge, concepts, language, metaphysics, mind,
mind / body and cosmology, especially the theory of origins and evolution in the division Metaphysics or Knowledge and Action of Journey in Being; and the
discussions of being and of technology and machines of the present division
2.3.1
Ontology
The following topics are useful:
Can a machine have life, mind or being? Here, it is implicit that life, mind or being refer to life, mind and being as we know them and not “primal” mental
elements or being. The primary reason for this specification is that due to the nature of life, mind, and being as slack concepts the answer without such
specification must be “yes.” It is further implicit that a machine is something that is built from any natural elements and is not restricted to the classical
idea of a deterministic machine. One answer to the restricted question is that, since the brain or body is a machine, it is obvious that a machine can have
mind, life, being! However, if by machine we mean something designed and built by agents that have mind, life and being to perform a specified
function, the answer is not clear. Specifically, it is not clear that the performance of the function is the equivalent of having mind and so on
What is it about living beings that makes for possession of mind? Note the following possibilities: multiple layers of organization from atoms / particles
up; deep grounding and adaptation of all layers; every cell in an organism is a variation of a single cell; every cell, with exceptions, contains the entire
genetic code
What is the nature of tools and machines; tools and machines as dynamic extensions vs. independent agents
The question of how to recognize mind is important
One approach is theoretical: to use the nature of mind and its characteristics to determine whether a machine, in virtue of its function, possesses the
specified characteristics. Note, that since there is mental content input-output replication does note make for mind; therefore, function must be
interpreted to include description of internal elements and processes. Problems with this approach include that mind is not a definite concept as noted in
the section Dimensions of Mind / Being: Introduction of Journey in Being; this, however, enhance recognition
Another, related, theoretical approach is what is called Theory of Mind i.e. understanding of how individuals recognize the presence of mind, life or being
in other individuals. The so-called Turing test is a sort of primitive test; there is no reason that the “machine” should be hidden from the “observer” who
only sees output from the machine; at the same time the observer need not be exposed to all internal details. The Turing test may be interpreted to rely
on perceptual similarity: comparison, empathy and intuition. It may be argued, with some validity, that recognition of mental phenomena in others is
automatic; however, this is not true for all mental phenomena: some mental phenomena are invisible and some may be purposely concealed. Thus, a
machine that had the qualities and degree of human mind ought to be able to deceive individuals and machines into thinking that the machine does not
have those qualities. There is also the issue of recognition in the case of other kinds of organism and in machines. When the idea of recognition is
extended to conceptual similarity, the test may be interpreted as the theoretical approaches mentioned earlier
When organisms and machines co-evolve, recognition will probably be automatic and not require theory. At the same time, theory will be useful
2.3.2
Knowledge
The following topics are useful:
Concepts8
In concepts [Section in Journey in Being], the idea of concept was introduced. It was noted there that concepts may receive over-articulation; however,
it was also noted that the proper degree of articulation is relative to the purpose. Here, it is appropriate to further analyze the idea of concept. The
purpose of the analysis is for use in machine intelligence and, since machine intelligence occurs in interaction with and is modeled on organic
intelligence, the study of concepts as they occur in both organisms and machine / computational systems is important
Concepts have narrow content in an individual’s representation of the world and broad content as a symbolic element of interaction among individuals
and the world
The intension of a concept is its meaning and the extension is the set of objects to which the concept may refer. These are rough definitions that may be
improved along a number of dimensions. I say that intension and extension are mutually determining over time; as a result a specific intension and
extension is, in general, never arrived despite the feeling that concepts are innate. Concepts are constructed; use becomes automatic; the origins of a
linguistic concept may be in the phase of pre-language; what is a construct functions, within limits, as and feels as though it is a priori
In machine intelligence, one use of concepts is as symbolic elements from which representations of knowledge or an area of expertise is constructed; in
a connectionist machine a concept would be identified [rather than defined] as an internal pattern that frequently arises in a variety of situations
In psychology, three main traditions of research are cognitive development originating with Piaget, classifying the world into categories in behaviorism,
and lexical semantics the study of concepts through words that are commonly used in their expression. For further information see the references cited
in the footnotes. Further information will be included in the present document dynamically as need arises in connection with development of research
tools and other applications
Knowledge representation9
7
Steven Sloman in the MIT Encyclopedia of the Cognitive Sciences, 2 nd edition, 1999, Robert A. Wilson and Frank C. Keil, eds.
8
Concepts by James A. Hampton in the MIT Encyclopedia of the Cognitive Sciences, 2nd edition, 1999, Robert A. Wilson and Frank C. Keil, eds.
Knowledge representation arises in the coding and use of areas of knowledge, sometimes expertise, for the purposes of use. Practical uses are expert
systems and theoretical, later, research uses include conceptual synthesis and concept recognition. I have developed some applications of the latter type
as described below in the applications
Knowledge representation requires: a vocabulary or set of terms and the related concepts that define the field covered; this system is called the
ontology. Both philosophical and practical aspects of the ontology are important; however, the development of practical systems may require, at least
temporary, suppression of philosophical concerns such as faithfulness, consistency, completeness. To a degree such concerns are introduced via defined
syntax and interpretation or semantics. The use of knowledge representation involves input / output computation such as: initial / final conditions;
problem statement / solution. The computation requires modeling. Depending on the context models may be more or less realistic and general: logical,
diagrammatic, dynamic in the sense of physics and so on. The greater the variety and realism or expressive power, the greater is the deductive
complexity and computational resources are limiting in this regard. One problem of expression is the distinction of dynamic from contextual elements
that is automatic for an organism but not at all for a machine. Such problems of knowledge representation may be addressed by the introduction of
realism in the cognitive process of the knowledge representation and dynamics; and by synthesis of such realism with knowledge representation. One
approach is the use of connectionist models that use connectionist architectures to model cognition. “Situated theories” use models of emergence of
behavior as a consequence of interaction with the world
Knowledge and concept representation and transformation: hierarchies, lists and matrices
Transformation of representation and organization
Linear and non-linear growth models
In commercial applications, database technology is used as the basis of knowledge representation; the ontology can be incorporated as data e.g. as a set
of propositions and or as code e.g. as methods of inference translated into algorithms
2.4
Tools and Tasks
Basis and definition e.g. the forms of information correspond to the forms of human intuition, formal representation and perception
2.4.1
Tools
Topics in Computer Science10 and Artificial Intelligence11; knowledge and conceptual tools: networks and libraries; dictionaries and encyclopedias; texts;
knowledge bases and representation – trees / databases, question and answer; reference systems – informal through tertiary and search tools
Hardware and environment issues12
2.4.2
Tasks
A System of Tasks13
Document management: storage, production, editing, publication: Internet, paper. Text system management: production, edit, update, multiple concept
representation and translation, index and contents; general symbolic processors
Intelligent assistance: assistant, interactive or dynamic, independent. Research: group process, communication, projects; funding, support; management
and administration; communication
Management: personal, enterprise
2.5
Implementation of Objectives
The present implementation of the objectives is:
2.5.1
Applications
Applications so far
The computer as environment: comparison with books and writing, leafing through electronic documents and search; learning and intuition; use of
massive computational storage, processing and representational capabilities; graphic interfaces: interactive, intelligent, customizable; an interface for
communication; file systems, their intuitive / logical structure; ubiquitous presence; automation; number codes and concepts; screen presence – large /
multiple screens and workspaces, partitioning, cut and paste; draft vs. production formats; document navigation; standard software as meaning
processors
Text / concept system: production, update and maintenance and publication; complex documents, propagating effects of changes; linking; generic
outlines and connectivity; text production and knowledge base templates – see links to the applications general, knowledge base and text production
templates; specific systems: journey in being, core curricula for science, engineering, and humanities; knowledge applications, encyclopedia,
encyclopedia as database, articles listing, conceptual and coded listing; human knowledge project; idealism / materialism databases of Evolution and
Design – see link to the application; scratchpad and conceptual experimentation
2.5.2
Plan
Plans are classed according to the Objectives: Machine Intelligence in Journey in Being [construction, transformation; the understanding that comes from
consideration of and actual construction and transformation; and application] and Theoretical and Conceptual Background
Plans include
Human Knowledge Project; see the document, Design for a Journey in Being
Use or deploy existing and commercial applications, then develop; exception: learning
Research management: personnel, projects, administration
Treatment planning
Managed care planning
Psychiatric management
Texts on CD/DVD: interactive pace, level, focus
Services: research, education – university, publication / online reference, knowledge
Professional services: planning, design, consulting; global – local
Application areas: politics, government, economics, social, technical, professional
Assistants, then interactive systems, then emulators and agents
Intelligent capability for defined application, then imitation and simulation of intelligent life
Knowledge systems, encyclopaedia [dynamic, link to literature, search;] informal, primary, secondary and tertiary literature
Assistant / dynamic element in knowledge
Knowledge and concept representation / transformation tools; hierarchies, lists, matrices
Machine as life, as being, as having mind, as conscious
9
Knowledge Representation by Patrick Hayes in the MIT Encyclopedia of the Cognitive Sciences, 2nd edition, 1999, Robert A. Wilson and Frank C. Keil, eds.
10
Topics in computer science: hardware systems, artificial intelligence , numerical analysis, software systems, mathematical foundations of computing,
analysis of algorithms, typography and computational models of language, general interest
11
Topics in artificial intelligence: General: production systems, neural networks, genetic algorithms and programming, computer vision, search including
heuristic search, planning, logic, knowledge representation and reasoning, managing / reasoning under uncertainty, common sense reasoning in logic,
Bayes networks, automatic planning and multi-agent communication, robotics and computer vision, machine learning, intelligent architectures connectionist or associative vs. von Neumann, and natural language understanding and processing, interactivity, narrative, and artificial intelligence.
Knowledge Representation: declarative knowledge representation methods. Time and action, non-monotonic logics, causality, inheritance and description
logics, ontologies, contexts, knowledge acquisition and reformulation, multiple views, abstraction, deduction vs. abduction, knowledge and other mental
attitudes. History: knowledge (declarative) vs. procedure based systems. Knowledge-based systems and applications: knowledge-based (expert) system
technology is the most widely-used application technology to emerge from AI. Topics: basics of knowledge based systems (KBS) and expert systems (ES);
technology transfer from research to industry; knowledge engineering, KB programming, knowledge acquisition methodology; evolution of the technology
as applied to business and government problems, current and future impact. Robotics and computer vision: manipulator kinematics and inverse kinematics;
manipulator dynamics, motion, and force control; motion planning and robot programming. Robot programming topics include: basics of motor control and
sensor characteristics; sensor fusion, model construction, and robust estimation; control regimes (fuzzy control and potential fields); active perception;
reactive planning architectures; various topics in sensor-based control, including vision-guided navigation. Some increasingly complex behaviors for mobile
robots: simple dead reckoning and reactivity, planning and map building, communication and cooperation. Issues and techniques of computer vision: image
formation, edge detection and image segmentation, stereo, motion, shape representation, recognition
12
Hardware classes and environment issues: hardware. Computation: processors, memory; storage; input / capture: keyboard, connectors, microphone /
audio, camera, video; output / display: monitor, projectors, speakers, printers; environment issues. Conditions: humidity and wetness, marine and
submerged; temperature... polar, desert; atmospheric: caustic, corrosive, dust and particulates, pressure extremes; space; industrial; acceleration and
shock. Mobile vs. stationary factors: size, area, weight; mounting and carriage; modularity – auto install; power – internal / external, local / imported;
durability; communications
Software classes: systems and communication. Systems Software: 1. Applications development system: development: languages, compilers, visual
environments, cross compilers, debugging and testing; 2. Operating systems: processor control, memory management, file management and linking; user
interface – GUI; network interface; device drivers. 3. Utilities. Communication Software: 1. Data communication: network management and operating
systems; data compression; Internet; 2. Telecommunications E-mail, fax, message center, video/teleconference; 3 Security and encryption; applications
software. Production Level Data Processing these have basis in human modes of perception, meaning and communication: word / text / font processors –
general, scientific, other; document management and linking; publishing, desktop publishing, typesetting; numeric, array and spreadsheet; database
management; graphic – draw, paint and photo, converters, general / scientific presentation, flow sheet / art libraries; CAD; video, sound, music and speech
– voice recognition, scanning and handwriting software, video and digital camera… and synthesis, musical instrument digital interface; multimedia playback, production and development. Knowledge and Knowledge Systems, Artificial Intelligence: Data / knowledge bases; AI / expert system, AI based
design and planning tools: genetic algorithms, neural nets. Specialized applications: Design, decision, planning and government. Science: mathematics and
statistics; science and engineering; arts and humanities. Education: interactive classroom simulation, computer based training, text and media
development. Law. Medicine: medical, psychiatric and management - managed care planning. Commerce: Business and finance, industry and agriculture,
service and service industries, and trade. Grants
13
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PHILOSOPHY OF MIND
Evolution and life; life design - a concept
LATEST REVISION AND COPYRIGHT
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SOURCES
When I study the works of others, I often make notes which vary in form from comments, to paraphrase to simply copying ideas; the purpose is usually to
learn – there is no other immediate purpose and so I may forget my sources. I am immersed in a culture of ideas that I absorb without complete
awareness. I did not create the ability to have ideas, or the notion of idea at the foundation of the tradition. I did not create the language in which I write.
Similarly there is a general system of thought that we do not cite even though we are dependent on it. Thus I am not always aware of my sources
If anyone would like to have a source cited, please write to me at [email protected]
One may want to be original yet, given the foundation upon which one builds – the culture of ideas, the ability to have ideas – the originality of an
individual is not much. And compared to others, my originality may be modest. And, in my view of the equivalence of being and the void there is no
originality at all. Yet I would like to be thought of as original and it would be a form of denial to not be aware of that. However, my claims to originality are
small; I feel I have been a discoverer rather than creator
FOOTNOTES