Reality Construction Through Info-Computation

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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

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Mälardalen University Sweden
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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
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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

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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

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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.

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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?

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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.

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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?

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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

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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

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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.

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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.

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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.

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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)

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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)
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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).

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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.
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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.

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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

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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

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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

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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.

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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.

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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

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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?

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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.

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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.

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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.

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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.

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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

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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.

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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.

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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

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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.

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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.

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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.

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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?

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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.

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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

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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.

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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.

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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

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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
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ADDITIONAL MATERIAL
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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.
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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.

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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.

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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.

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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