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Title: Reality Construction Through Info-Computation


1
Reality Construction Through Info-Computation
AISB50 Celebrating 50 years of the AISB 1st
4th April 2014, Goldsmiths, University of London
Representation of Reality Humans, Animals and
Machines Symposium
  • Gordana Dodig Crnkovic
  • Professor of Computer Science
  • Mälardalen University, School of Innovation,
    Design and Engineering
  • gordana.dodig-crnkovic_at_mdh.se

2
Mälardalen University Sweden
3
REALITY
  • What is reality for an agent?
  • How does reality of a bacterium differ from a
    reality of a human brain?
  • Do we need representation in order to understand
    reality?

Representation of Reality Humans, Animals and
Machines Symposium
4
REALITY
  • 1 something that actually exists
  • Synonyms actuality, case, materiality
  • Related Words certainty, inevitability
    circumstance, event, occurrence, phenomenon
    element, item, particular, thing
  • Near Antonyms eventuality, possibility,
    potentiality, probability
  • Antonymsfantasy (also phantasy), fiction,
    illusion
  • 2 the fact of being or of being real
  • Synonyms actuality, corporality, corporeality,
    reality, subsistence, thingness
  • Related Words realness presence, prevalence
  • Near Antonyms absence, potentiality, virtuality
  • Antonyms inexistence, nonbeing, nonexistence,
    nothingness, unreality

5
REALITY
  • 3 the quality of being actual
  • Synonyms actuality, factuality, materiality
  • Related Words authenticity, genuineness, truth,
    verity
  • Near Antonyms fancy, fantasy, fiction,
    surreality
  • Antonyms irreality, unreality
  • 4 one that has a real and independent existence
  • Synonyms being, substance, thing
  • Related Words body, subject material, matter,
    quantity, stuff
  • Near Antonyms nonentity

6
WHAT IS REALITY (FOR AN AGENT)?
  • When discussing cognition as a bioinformatic
    process of special interest, we use the notion of
    agent, i.e. a system able to act on its own
    behalf 1. Agency in biological systems has
    been explored in 23. The world (reality) as
    it appears to an agent depends on the type of
    interaction through which the agent acquires
    information and on agents own information-processi
    ng 1.
  • Groups of agents communicate by exchanging
    messages (information) that help them coordinate
    their actions based on the (partial) information
    they possess and share as a part of social
    cognition.

7
COGNITION AS LIFE
  • Agency and cognition is a property of all living
    organisms.
  • Agents themselves can consist of networks of
    agents, recursively. A single biological cell
    consists of network of agents. Networks of cells
    form tissues that form organs that form organisms
    that organize in ecologies.
  • The question is how artifactual agents should be
    built in order to possess different degrees of
    cognition and eventually even consciousness. Is
    it possible at all, for an artifactual agent to
    be cognitive given that cognition in living
    organisms is a deeply biologically rooted process
    connected to survival?

8
LANGUAGE AS A TOOL OF HIGH LEVEL COGNITION
  • Increasing levels of cognition developed in
    living organisms evolutionary, starting from
    basic automatic minimally adaptive behaviours
    such as found in bacteria and even insects (even
    though insects have nervous system and brain,
    they lack the limbic system that controls
    emotional response to physical stimuli,
    suggesting they don't process physical stimuli
    emotionally) to increasingly complex behaviour in
    higher organisms such as mammals.

9
LANGUAGE AS A TOOL OF HIGH LEVEL COGNITION
  • Recent advances in natural language processing,
    such as Watson computer that wins Geopardy,
    present examples of developments towards machines
    capable of both understanding natural language
    and speaking in a human way.
  • Along with reasoning, language is often
    considered a high-level cognitive activity that
    only humans are capable of.
  • Can AI jump over evolutionary steps in the
    development of cognition and base language use on
    pure machine learning from vast data sets?

10
INFO-COMPUTATIONAL FRAMEWORK FOR STUDY OF
COGNITION
  • The framework for the discussion here is the
    computing nature in the form of
    info-computationalism.
  • It takes reality to be information for an agent
    with a dynamics of information understood as
    computation.
  • Information is a structure and computation its
    dynamics.
  • Information is observer relative and so is
    computation. 145

11
INFO-COMPUTATIONAL FRAMEWORK FOR STUDY OF
COGNITION
  • Cognition is studied as information processing in
    such simple organisms as bacteria 6, 7 as
    well as cognitive processes in other, more
    complex multicellular life forms.
  • We discuss computational mind and consciousness
    that have recently been widely debated in the
    work of Giulio Tononi 8 and Christoph Koch. 9

12
INFO-COMPUTATIONAL FRAMEWORK FOR STUDY OF
COGNITION
  • While the idea that cognition is a biological
    process in all living organisms, as argued by
    Humberto Maturana and Francisco Varela 10,
    11, it is not at all clear that all cognitive
    processes in different kinds of organisms are
    accompanied by anything akin to (human)
    consciousness.
  • The suggestion is made that cognitive agents with
    nervous systems are the step in evolution that
    first enabled consciousness of the kind that
    humans possess. Argument is advanced that
    ascribing consciousness to the whole of the
    universe is not justified.

13
REALITY AS INFORMATION FOR AN AGENT
  • Defining reality as information leaves us with
    the question what is it in the world that
    corresponds to information and its dynamics,
    computation? How do we model information/
    computation? Answers are many and they are not
    unambiguous.

14
INFORMATION, COMPUTATION, COGNITION
  • We can compare the present situation regarding
    information, computation and cognition with the
    history of the development of other basic
    scientific concepts. Ideas about matter, energy,
    space and time in physics have their history. The
    same is true of the idea of number in mathematics
    or the idea of life in biology.
  • So, we should not be surprised to notice the
    development in the theory of computation that
    goes hand in hand with the development of
    information science, cognitive science,
    computability, robotics, new computational
    devices and new domains of the real world that
    can be understood info-computationally.

15
LIFE AS INFO-COMPUTATIONAL GENERATIVE PROCESS OF
COGNITION AT DIFFERENT LEVELS OF ORGANIZATION
  • An agent is an entity capable of acting on its
    own behalf. It can be seen as an "actor" in the
    Actor model of computation in which "actors" are
    the basic elements of concurrent computation
    exchanging messages, capable of making local
    decisions and creating new actors. Computation is
    thus distributed in space where computational
    units communicate asynchronously and the entire
    computation is not in any well-defined state. (An
    actor can have information about other actors
    that it has received in a message about what it
    was like when the message was sent.) (Hewitt,
    2012)

16
COGNITIVE INFORMATION PROCESSING THEORY OF
LEARNING ACCORDING TO (GAGNÉ, 1985)
  • This is an old and simplistic idea of cognition
    as information processing. Missing in this scheme
    are feedback loops that are absolutely essential
    for cognition and learning. Also missing is
    information integration from different sensors
    and couplings to actuators. Memory is not a
    passive storage but active ingredient in
    perception, that is both used for recognition and
    anticipation.

Cognitive / Information Processing Theory of
Learning according to (Gagné, 1985)
17
WHAT IS REALITY (FOR AN AGENT)?
  • Whatever is a reality today, whatever you touch
    and believe in and that seems real for you today,
    is going to be, like the reality of yesterday, an
    illusion tomorrow.
  • Luigi Pirandello, Six Characters in Search of an
    Author
  • The father, in Six Characters in Search of an
    Author, act 3 (1921).

18
WHAT IS REALITY (FOR AN AGENT)?
  • Would we agree that reality resides in that which
    is now, taking into account that our cognitive
    apparatus has a finite resolution in time (it
    might be as much as 7 seconds delay between
    decision and action) where now would be
    measured, perhaps in minutes?
  • What about phenomena that change more slowly? For
    such phenomena, now could be days, or years
    depending on the phenomenon. But if it is longer
    time than what we immediately observe, then the
    reality must be based not only on current
    perception/understanding but also on memory.
  • How about reality of future (anticipated) events?
    What is a difference of a highly probable event
    (such that the Earth revolves the Sun hundred
    years from now)?

Chun Siong Soon, Marcel Brass, Hans-Jochen Heinze
John-Dylan Haynes, Unconscious Determinants of
Free Decisions in the Human Brain. Nature
Neuroscience, April 13th, 2008.
19
WHAT IS REALITY (FOR AN AGENT)?
  • Undoubtedly, we base our decisions/actions on
    both memory, current observations and
    anticipations.
  • There is a difference between fiction or virtual
    reality and anticipated event based on firm past
    evidence.
  • Degree of reality varies between anticipated
    highly probable event and fiction or virtual
    representation of any state of similar event.

20
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • In his new book, Explaining the Computational
    Mind 49 Marcin Milkowski portrays current state
    of the ideas about computational mind. The author
    presents and systematically dissects number of
    misconceptions about what is computation, clearly
    placing both neural networks and dynamical
    systems into the domain of computational. This is
    something that some philosophers would deny,
    while practitioners would agree with. 36

21
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • Milkowski proposes his own view of computational
    models in the following
  • (O)n my mechanistic account, only one level of
    the mechanism the so-called isolated level is
    explained in computational terms. The rest of the
    mechanism is not computational, and, indeed,
    according to the norms of this kind of
    explanation, it cannot be computational through
    and through.
  • In this article I argue that this
    one-level-approach is not adequate for natural
    (intrinsic) computation which appear in hierarchy
    of levels. The reason why Milkowski tries to
    avoid multiplicity of computational levels is a
    fear of computationalism being trivial

22
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • In this article I argue that this
    one-level-approach is not adequate for natural
    (intrinsic) computation which appear in hierarchy
    of levels. The reason why Milkowski tries to
    avoid multiplicity of computational levels is a
    fear of computationalism being trivial
  • the bottoming-out principle of mechanistic
    explanation () says that a phenomenon has to be
    explained as constituted by some other phenomenon
    than itself. For a pancomputationalist, this
    means that there must be a distinction between
    lower-level, or basic, computations and the
    higher level ones. Should pancomputationalism be
    unable to mark this distinction, it will be
    explanatorily vacuous. 50

23
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • From the above I infer that the model of
    computation, which Milkowski assumes in his book,
    is a top-down, designed computation. Even though
    he rightly argues that neural networks are
    computational models and even dynamical systems
    can be understood as computational, Milkowski
    does not think of intrinsic computation as
    grounded in physical process driven by causal
    mechanism, characteristics of computing nature.

24
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • The fundamental question that worries Milkowski
    is the grounding problem that can lead to the
    conclusion about triviality. I will argue that
    this really is a non-problem.
  • To start with, grounding is always anchored in an
    agent who is the narrator of the explanation. The
    narrator choses the granularity of the account.
    No picture has infinite granularity and nothing
    hinders to imagine even lower levels of existence
    (such as more and more elementary particles).
    This means that grounding is done over and over
    again in all sciences.

25
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • When constructing computational models,
    Milkowskis focus on only one layer is
    pragmatically justified, but not a matter of
    principle. Even though one can reconstruct many
    intrinsic computational layers in the human brain
    (depending on the granularity of the account),
    for an observer/narrator often one layer is in
    focus at a time. In such simplified models the
    layers above and below, even though
    computational, are sketchy and used to represent
    constraints and not mechanisms. That is at least
    the case in designed computation as found in
    conventional computers. But e.g. looking at the
    experimental work of Subrata Ghosh et al.
    building a functional model of brain, we find
    twelve-layer computational architecture applied.
    51

26
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • What is at stake in a theory of implementation?
    The main problem seems to me exactly the
    opposite.
  • It is not so interesting to study how brain
    implements computation top-down (how do we know
    112) but how intrinsic information processing,
    that is evidently going on in the brain can be
    interpreted as computation. What are the
    characteristics of that new kind of computation
    that information processes in the brain
    constitute?

27
COMPUTATION ALL THE WAY DOWN TO QUANTUM
  • In that sense of bottom-up intrinsic computation
    Chalmers characterization holds, 54 p. 326
  • A physical system implements a given computation
    when the causal structure of the physical system
    mirrors the formal structure of the computation.
  • This position is called the Standard Position
    (SP) by Sprevak. 55 p. 112. It is applicable to
    intrinsic computation (bottom up,
    natural/intrinsic), but not to designed
    conventional computation (top-down) as this
    mirroring would be a very complex process of
    interpretation, coding, decoding and
    interpretation again.
  • Thus, not only neurons and whole brains compute
    (in the framework of computing nature) but also
    the rest of nature computes at variety of levels
    of organization.

28
COMPUTATIONAL MODELS OF MIND EXCULPATED
  • Sprevaks 55 p. 108 concerns about
    computationalism
  • (R1) Clarity Ultimately, the foundations of our
    sciences should be clear. Computationalism is
    suspected to lack clarity.
  • (R2) Response to triviality arguments (O)ur
    conventional understanding of the notion of
    computational implementation is threatened by
    triviality arguments. Computationalism is
    accused of triviality.
  • (R3) Naturalistic foundations The ultimate aim
    of cognitive science is to offer, not just any
    explanation of mental phenomena, but a
    naturalistic explanation of the mind.
    Computationalism is questioned for being formal
    and unnatural.

29
COMPUTATIONAL MODELS OF MIND EXCULPATED
  • Let me summarize the distinction between
    intrinsic /natural/ spontaneous computation and
    designed computation used in our technological
    devices.
  • In the info-computationalism, that is a variety
    of pancomputationalism, physical nature
    spontaneously performs different kinds of
    computations (information dynamics) at different
    levels of organization. This is intrinsic,
    natural computation and is specific for a given
    physical system. Intrinsic computation(s) of a
    physical system can be used for designed
    computation, such as one found in computational
    machinery, but it is far from all computation
    that can be found in nature.

30
COMPUTATIONAL MODELS OF MIND EXCULPATED
  • Why is natural computationalism not vacuous?
  • For the same reason that physics is not vacuous
    which makes the claim that the entire physical
    universe is material. Now we will not enter the
    topic of ordinary matter-energy vs. dark
    matter-energy. Those are all considered to be the
    same kind of phenomena natural phenomena that
    must be studied with methods of physics.
  • Why is natural computationalism not vacuous? For
    the same reason that physics is not vacuous which
    makes the claim that the entire physical universe
    is material. Now we will not enter the topic of
    ordinary matter-energy vs. dark matter-energy.
    Those are all considered to be the same kind of
    phenomena natural phenomena that must be
    studied with methods of physics.

31
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • Some computational models of consciousness 8,
    58, 59, 9 seem to lead to panpsychism - a
    phenomenon defined as follows
  • Panpsychism is the doctrine that mind is a
    fundamental feature of the world which exists
    throughout the universe. 60

32
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • Pancomputationalism (natural computationalism,
    computing nature) is the doctrine that whole of
    the universe, every physical system, computes. In
    the words of 61
  • Which physical systems perform computations?
    According to pancomputationalism, they all do.
    Even rocks, hurricanes, and planetary systems
    contrary to appearances are computing systems.
    Pancomputationalism is quite popular among some
    philosophers and physicists.

33
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • Info-computationalism starts bottom-up, from
    natural processes understood as computation. It
    means that computation appears as quantum,
    chemical, biological-cognitive, etc.
  • Only those transformations of informational
    structures that correspond to intrinsic processes
    in natural systems qualify as computation.

34
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • Given the argument for info-computational
    modelling of nature, and the argument that every
    living organism possesses some extent of
    cognition one can ask why should we not do
    similar move and ascribe consciousness to the
    whole of the universe (hypothesis called
    panpsychism)? Searle describes consciousness as
    follows
  • Consciousness consists of states of awareness
    or sentience or feeling. These typically begin in
    the morning when you wake up from a dreamless
    sleep and go on all day until you go to sleep or
    otherwise become 'unconscious.' 62

35
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • The simple answer why panpsychism is not a good
    idea is in the case of panpsychism we have no
    good model. Unlike computational models of
    physical and thus biological and cognitive
    processes we have no good psychical models.
  • In fact only naturalists accounts of
    consciousness provide models, others prefer to
    see consciousness as totally inexplicable in
    rational terms, a mystery.
  • From the naturalist, knowledge generation point
    of view, trying to understand everything as
    psyche got it backwards we do not know what to
    do after the very first move, other than to say
    that it is mysterious.

36
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • The simple answer why panpsychism is not a good
    idea is in the case of panpsychism we have no
    good model. Unlike computational models of
    physical and thus biological and cognitive
    processes we have no good psychical models.
  • In fact only naturalists accounts of
    consciousness provide models, others prefer to
    see consciousness as totally inexplicable in
    rational terms, a mystery.
  • From the naturalist, knowledge generation point
    of view, trying to understand everything as
    psyche got it backwards we do not know what to
    do after the very first move, other than to say
    that it is mysterious.

37
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • On the contrary, if we try to understand psyche
    or better to say mind and consciousness as
    manifestations of physical info-computational
    processes in the nervous system of a cognizing
    agent, we immediately have an arsenal of
    modelling tools to address the problem with and
    successively and systematically learn more about
    it, even construct artefacts (such as cognitive
    robots) and test it.

38
WHY PANCOMPUTATIONALISM IS USEFUL AND PANPSYCHISM
IS NOT
  • That is the main reason why panpsychism is not a
    good scientific hypothesis. Instead of opening
    all doors for investigation, it declares
    consciousness permeating the entire universe and
    that's it. One can always generalize concepts if
    they lead to better understanding and enable
    further modelling. But generalizations of the
    idea of psyche is akin to homeopathic procedure
    diluting it to concentrations close to zero, and
    that will not give us anything in terms of
    understanding of mechanisms of mind.
  • Moreover, as a theory panpsychism belongs to
    medieval tradition that which is to be
    explained is postulated. I wonder how would
    anyone ever get unconscious in a conscious
    universe? What would be the difference between
    human consciousness and the consciousness of a
    bacterium or even a consciousness of vacuum?

39
CONCLUSIONS AND FUTURE WORK
  • Questions that we posed in the beginning of the
    article What is reality for an agent? How does
    reality of a bacterium differ from a reality of a
    human brain? Do we need representation in order
    to understand reality? led us to the discussion
    of info-computational models of cognition and
    consciousness.
  • When talking about models of cognition, the very
    mention of computationalism typically evokes
    reactions against Turing machine model of the
    brain and perceived determinism of computation.
    Neither of those two problems affects natural
    computation or computing nature where model of
    computation is broader than deterministic symbol
    manipulation.

40
CONCLUSIONS AND FUTURE WORK
  • Computing nature consists of physical structures
    that form levels of organization, on which
    computation processes differ. It has been argued
    that on the lower levels of organization finite
    automata or Turing machines might be adequate,
    while on the level of the whole-brain non-Turing
    computation is necessary, according to Andre
    Ehresmann 63 and Subrata Ghosh et al. 51

41
CONCLUSIONS AND FUTURE WORK
  • Finally, an argument is advanced that the idea of
    panpsychism as a consequence of computational
    models by no means should be understood as
    necessary. It rather seems to be an artefact of
    the model and there is a variety of ways to
    correct the model so that non-physical properties
    do not follow.

42
CONCLUSIONS AND FUTURE WORK
  • For the future a lot of work remains to be done,
    especially on the connections between the low
    level cognitive processes and the high level
    ones. It is important to find relations between
    cognition and consciousness and the detailed
    picture of info-computational mechanisms behind
    those phenomena.

43
REFERENCES
  • http//www.idt.mdh.se/gdc/work/AISB2014-02-20-1-G
    ordanaDC.pdf
  • https//www.doc.gold.ac.uk/aisb50/s23
  • E. Ben-Jacob, Bacterial Complexity More Is
    Different on All Levels, in Systems Biology- The
    Challenge of Complexity, S. Nakanishi, R.
    Kageyama, and D. Watanabe, Eds. Tokyo Berlin
    Heidelberg New York Springer, 2009, pp. 2535.
  • E. Ben-Jacob, Learning from Bacteria about
    Natural Information Processing, Ann. N. Y. Acad.
    Sci., vol. 1178, pp. 7890, 2009.
  • G. Tononi, The Integrated Information Theory of
    Consciousness An Updated Account, Arch. Ital.
    Biol., vol. 150, no. 2/3, pp. 290326, 2012.
  • C. Koch, Consciousness - Confessions of a
    Romantic Reductionist. Cambridge Mass. MIT
    Press, 2012.
  • http//www.neuroinformatics2013.org
    Neuroinformatics conference 2013

44
A COMPUTABLE UNIVERSE
45
Computation, Information, CognitionEditor(s)
Gordana Dodig Crnkovic and Susan Stuart,
Cambridge Scholars Publishing, 2007
COMPUTING NATURE
Information and ComputationEditor(s) Gordana
Dodig Crnkovic and Mark Burgin, World Scientific,
2011
Computing NatureEditor(s) Gordana Dodig
Crnkovic and Raffaela Giovagnoli, Springer, 2013
46
Special Issue of the Journal Entropy Selected
Papers from Symposium on Natural/Unconventional
Computing and Its Philosophical Significance
Giulio Chiribella, Giacomo Mauro DAriano and
Paolo Perinotti Quantum Theory, Namely the Pure
and Reversible Theory of Information Susan
Stepney Programming Unconventional Computers
Dynamics, Development, Self-Reference Gordana
Dodig Crnkovic and Mark Burgin Complementarity
of Axiomatics and Construction Hector Zenil,
Carlos Gershenson, James A. R. Marshall and David
A. Rosenblueth Life as Thermodynamic Evidence of
Algorithmic Structure in Natural
Environments Andrée C. Ehresmann MENS, an
Info-Computational Model for (Neuro-)cognitive
Systems Capable of Creativity Gordana Dodig
Crnkovic and Raffaela Giovagnoli, Editorial
Natural/Unconventional Computing and Its
Philosophical Significance
47
Special issue of the journal Information
Information and Energy/Matter
Vlatko Vedral Information and Physics Philip
Goyal Information PhysicsTowards a New
Conception of Physical Reality Chris Fields If
Physics Is an Information Science, What Is an
Observer? Gerhard Luhn The Causal-Compositional
Concept of Information Part I. Elementary Theory
From Decompositional Physics to Compositional
Information Koichiro Matsuno and Stanley N.
Salthe Chemical Affinity as Material Agency for
Naturalizing Contextual Meaning Joseph E.
Brenner On Representation in Information
Theory Makoto Yoshitake and Yasufumi Saruwatari
Extensional Information Articulation from the
Universe Christopher D. Fiorillo Beyond Bayes
On the Need for a Unified and Jaynesian
Definition of Probability and Information within
Neuroscience William A. Phillips Self-Organized
Complexity and Coherent Infomax from the
Viewpoint of Jayness Probability Theory Hector
Zenil Information Theory and Computational
Thermodynamics Lessons for Biology from
Physics Joseph E. Brenner On Representation in
Information Theory Gordana Dodig Crnkovic,
Editorial Information and Energy/Matter
48
Connections to the contemporary work
  • Informational structural realism (Luciano
    Floridi)
  • Unconventional computing physical computing of
    natural systems (Susan Stepney)
  • Agent-centred information self-structuring (Bill
    Phillips)
  • Informational reality for an agent (Vlatko
    Vedral)
  • Info-computational model for (neuro-)cognitive
    systems up to creativity (Andrée C. Ehresmann)
  • Information integration and differentiation
    (Marcin Schröder)
  • Rao Mikkilineni Designing a New Class of
    Distributed Systems (SpringerBriefs in Electrical
    and Computer Engineering)
  • Emergent Computation (Bruce MacLennan)

http//www.researchtoaction.org/live/wp-content/up
loads/2011/05/networks1.jpg
49
ADDITIONAL MATERIAL
50
ACTOR MODEL OF CONCURRENT DISTRIBUTED COMPUTATION
In the Actor Model Hewitt, Bishop and Steiger
1973 Hewitt 2010, computation is conceived as
distributed in space, where computational devices
communicate asynchronously and the entire
computation is not in any well-defined state.
(An Actor can have information about other Actors
that it has received in a message about what it
was like when the message was sent.) Turing's
Model is a special case of the Actor Model.
(Hewitt, 2012)
Hewitts computational devices are conceived as
computational agents informational structures
capable of acting on their own behalf.
51
ACTOR MODEL OF CONCURRENT DISTRIBUTED COMPUTATION
  • Actors are the universal primitives of
    concurrent distributed digital computation. In
    response to a message that it receives, an Actor
    can make local decisions, create more Actors,
    send more messages, and designate how to respond
    to the next message received.
  • For Hewitt Actors rise to the level of Agenthood
    when they competently process expressions
  • for commitments including the following
  • Contracts, Announcements, Beliefs, Goals,
    Intentions, Plans,
  • Policies, Procedures, Requests, Queries.
  • In other words, his agents are human-like.

52
LIFE AS INFO-COMPUTATIONAL GENERATIVE PROCESS OF
COGNITION AT DIFFERENT LEVELS OF ORGANIZATION
  • This paper presents a study within
    info-computational constructive framework of the
    life process as ltknowledgegt generation in living
    agents from the simplest living organisms to the
    most complex ones. Here ltknowledgegt of a
    primitive life form is very basic indeed it is
    ltknowledgegt how to act in the world. An amoeba
    ltknowsgt how to search for food and how to avoid
    dangers.

53
LIVING AGENTS
  • A living agent is a special kind of actor that
    can reproduce and that is capable of undergoing
    at least one thermodynamic work cycle. (Kauffman,
    2000)
  • This definition differs from the common belief
    that (living) agency requires beliefs and
    desires, unless we ascribe some primitive form of
    ltbeliefgt and ltdesiregt even to a very simple
    living agents such as bacteria. The fact is that
    they act on some kind of ltanticipationgt and
    according to some ltpreferencesgt which might be
    automatic in a sense that they directly derive
    from the organisms morphology. Even the simplest
    living beings act on their own behalf.

54
LIVING AGENTS
  • Although a detailed physical account of the
    agents capacity to perform work cycles and so
    persist in the world is central for understanding
    of life/cognition, as (Kauffman, 2000) (Deacon,
    2007) have argued in detail, this work is
    primarily interested of the info-computational
    aspects of life.
  • Info-computational approach takes information an
    computation to be the two basic building block
    concepts, corresponding to structure and process,
    being and becoming.
  • Given that there is no information without
    physical implementation (Landauer, 1991),
    computation as the dynamics of information is the
    execution of physical laws.

55
LIVING AGENTS
  • Kauffmans concept of agency (also adopted by
    Deacon) suggests the possibility that life can be
    derived from physics. That is not the same as to
    claim that life can be reduced to physics that is
    obviously false.
  • However, in deriving life from physics one may
    expect that both our understanding of life as
    well as physics will change.
  • We witness the emergence of information physics
    (Goyal, 2012) (Chiribella, G. DAriano, G.M.
    Perinotti, 2012) as a possible reformulation of
    physics that may bring physics and life/cognition
    closer to each other. This development smoothly
    connects to info-computational understanding of
    nature (Dodig-Crnkovic Giovagnoli, 2013).

56
THE COMPUTING NATURE
  • Life can be analyzed as cognitive processes
    unfolding in a layered structure of nested
    information network hierarchies with
    corresponding computational dynamics (information
    processes) from molecular, to cellular,
    organismic and social levels.
  • In order to construct life as cognitive process
    we will introduce two fundamental theories about
    the nature of the universe and propose their
    synthesis
  • The first one with focus on processes is the
    idea of computing universe (naturalist
    computationalism/ pancomputationalism) in which
    one sees the dynamics of physical states in
    nature as information processing (natural
    computation).

57
THE COMPUTING NATURE
  • The parallel fundamental theory with focus on
    structures is Informational structural realism
    (Floridi, 2003) that takes information to be the
    fabric of the universe (for an agent).
  • Combining definitions of Bateson
  • information is a difference that makes a
    difference (Bateson, 1972)
  • and Hewitt
  • Information expresses the fact that a system is
    in a certain configuration that is correlated to
    the configuration of another system. Any physical
    system may contain information about another
    physical system. (Hewitt, 2007), we get
  • information is defined as the difference in one
    physical system that makes the difference in
    another physical system.

58
THE COMPUTING NATURE
  • information is defined as the difference in one
    physical system that makes the difference in
    another physical system.
  • This implies relational character of information
    and thus agent-dependency in agent-based or
    actor model.
  • As a synthesis of informational structural
    realism and natural computationalism,
    info-computational structuralism adopts two basic
    concepts information (as a structure) and
    computation (as a dynamics of an informational
    structure) (Dodig-Crnkovic, 2011) (Chaitin,
    2007).
  • In consequence the process of dynamical changes
    of the universe makes the universe a huge
    computational network where computation is
    information processing. (Dodig-Crnkovic
    Giovagnoli, 2013) Information and computation are
    two basic and inseparable elements necessary for
    naturalizing cognition and ltknowledgegt.
    (Dodig-Crnkovic, 2009)

59
THE COMPUTING NATURE
  • Agents - systems able to act on their own behalf
    and make sense (use) of information are of
    special interest with respect to ltknowledgegt
    generation.
  • This relates to the ideas of participatory
    universe, (Wheeler, 1990) endophysics (Rössler,
    1998) and observer-dependent ltknowledgegt
    production.

60
MORPHOLOGICAL COMPUTATION FROM SIMPLEST TO THE
MOST COMPLEX ORGANISMS
  • In the computing nature, ltknowledgegt generation
    should be studied as a natural process. That is
    the main idea of Naturalized epistemology (Harms,
    2006), where the subject matter is not our
    concept of ltknowledgegt, but the knowledge itself
    as it appears in the world as specific
    informational structures of an agent.
  • Maturana and Varela were the first to suggest
    that knowledge is a biological phenomenon. They
    argued that life should be understood as a
    process of cognition, which enables an organism
    to adapt and survive in the changing environment.
    (Maturana Varela, 1980)

61
NETWORK AGENT/ACTOR MODELLS
62
Human brain is biological information processor -
network of neurons processing information
http//neuralethes-en.blogspot.se/2012/04/human-co
nnectome-project.html Human Connectome Project
63
Info-computational framework connecting
informational structures and processes from
quantum physics to living organisms and
societies
  • Nature is described as a complex informational
    structure for a cognizing agent.
  • Computation is information dynamics (information
    processing) constrained and governed by the laws
    of physics on the fundamental level.
  • Information is the difference in one information
    structure that makes a difference in another
    information structure.

64
COMPUTING NATURE
  • The basic idea of computing nature is that all
    processes taking place in physical world can be
    described as computational processes from the
    world of quantum mechanics to living organisms,
    their societies and ecologies. Emphasis is on
    regularities and typical behaviors.
  • Even though we all have our subjective reasons
    why we move and how we do that, from the
    bird-eye-view movements of inhabitants in a city
    show big regularities.
  • In order to understand big picture and behavior
    of societies, we take computational approach
    based on data and information.
  • See the work of Albert-László Barabási who
    studies networks on different scales
  • http//www.barabasilab.com/pubs-talks.php

65
COMPUTATION AS INFORMATION PROCESSING
  • Info-computational approach takes information as
    the primary stuff of the universe, and
    computation is as time-dependent behavior
    (dynamics) of information.
  • This results in a Dual-aspect Universe
    informational structure with computational
    dynamics. (Info-Computationalism, Dodig Crnkovic)
  • Information and computation are closely related
    no computation without information, and no
    information without dynamics (computation).

66
COGNITION AS COMPUTATION
Information/computation mechanisms are
fundamental for evolution of intelligent agents.
Their role is to adapt the physical structure and
behavior that will increase organisms chances of
survival, or otherwise induce some other behavior
that might be a preference of an agent. In this
pragmatic framework, meaning in general is use,
which is also the case with meaning of
information.
http//www.worldhealth.net/news/
hormone-therapy-helps-improve-cognition
http//www.ritholtz.com/blog/wp-content/uploads/ 2
012/04/my-brain-hurts.png
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