General Understanding of Information

4. März 2011 Informationsphilosophie. Information und urbanes Systeme 1
Information:
Brücke
zwischen
Philosophy: Philosophy of Information
Fakultät 13, Hochschule München, Winter Semester 2016-2017
José María Díaz Nafría (Universidad de León, Spain)

A General Understanding of Information
1. Groundings
a) The information age and the language of
information (historical perspective)
b) The Frame of the Mathematical Theory of
Communication (film: Communication Primmer)
c) Semantic information and Algorithmic Theory
of Information
d) Information in the sciences
2. Information throughout the ladder of
complexity
a) The progressive perspective
b) Regressive perspective
3. Presentations
2A General Understanding of Information

The origins of the information concept
Latin and Greek roots
• Material information case (Hefestos)
• Observation case (Subject)
• Speaking or Instructional case (communication)
Plato’s Forms
• Otherworldliness
• Digital communication model
Aristotle’s Matter and Form
• Form (actuality) and Matter (potentiality)
• The individuality of real things. Particular
form: essences
• General essences: being of species that can be
inductively grasped

Bibliographic tips
4
• FLORIDI, L. (2010). Information. A very short introduction. Oxford:
Oxford University Press.
• DÍAZ NAFRÍA, J.M. (2011). Messages in an open universe. in Capurro, R.
and Holgate (eds.). Messages and messangers. Angeletics as an approach
to the phenomenology of of communication. Munich: W.Fink, 195-229.
• DIAZ NAFRIA (2011): Information, a multidimensional reality, in Curras and
Lloret. Nuria LLORET(2011). Systems Science and Collaborative
Information Systems. Hershey PA, USA: IGI Global
• DÍAZ NAFRÍA, J.M. (2010). Information: a multidimensional concern.
TripleC, 8(1), 77-108 [online http://triple-
c.at/index.php/tripleC/article/view/76/168].
• HOFKIRCHNER, W. (2010). Twenty Questions About a Unified Theory of
Information. Arizona: Emergent publications.
• BURGIN, M. (2010). Theory of Information. Fundamentality, Diversity and
Unification. Singapore: World Scientific Publishing.

5
• LYRE, Holger (2002). Informationstheorie. Eine philosophisch-
naturwissenschftliche Einführung. Munich: W.Fink Verlag.
• DÍAZ NAFRIA, J.M., et al. (Koord.) (2010). Glossarium BITri: glossary of
Concepts, metaphors, theories and problems concerning information.
León: Universidad de León [online
http://glossarium.bitrum.unileon.es/glossary, http://wp.me/pzKNC-66]
• DÍAZ NAFRÍA and SALTO (2009). What is information? An interdisciplinary
approach. Special issue TripleC, 7(2) [online http://wp.me/pzKNC-2G].
Bibliographic tips

6
1 5 10 50 100 500 1000
0500100015002000250030003500
TF
Frequency
glossariumBITri (Interdisciplinary Glossary)

7

8
information
theory
know ledge
concept
communication
use

Invitation to Complementary Activity
Social Networks (2012): from indignation to change
Social Networks (2013): from communication to solidarity
Social Networks (2014): globalization and inequality
glossariumBITri (2015): How to write interdisciplinary papers?
1st - 3rd ed. Sept.2012-2014;
4th ed. Sept.2015, Santa Elena, Ecuador
Cooperation: HM - ULE – UNED – TUW – UPSE…
With: Prof. R.E. Zimmermann (HM)
Prof. J.M. Díaz Nafría (ULE)
Prof. P. Hofkirchner (TUW), et al.
Credits: 2 ECTS

PRIMER
E&R Programme
Education & Research programme
International Summer Academies
Support: EU (under request)
Period: 2017-2020
Venues: Spain, Austria, Greece, Germany

I. Groundings (the development of
the information understanding)
0. Towards a general understanding of
information
1. Development of the information concept:
Plato, Aristotle, Middle Ages, Modernity,
(technique and physics)
2. General understanding of Information
3. Mathematical Theory of Communication
4. Algorithmic Theory of Information
5. Information in the sciences

I.0 Towards a General
Understanding of Information
• In the Information Era we should be able to
understand what information really means
(comparison to the Iron Era: iron vs cupper)
• The Nature of information is not solved
• Information can be considered as something
mediating between Objects and Subjects
• To this end, a general understanding of Objects
and Subjects is also needed.

I.0 Information concept
(immaterial)
13
Time
Information
t1 t2 t3
Subject of the change
(in the awareness)
Object:
In opposition to
the subject of
the change (awareness)

(0) Information concept
(tangible)
14
Time
t1 t2 t3
Information
Subject of the change
Object:
In opposition to
the Subject
of the change
(model + hammer)

(0) Clarifying
• Form: a particular configuration/Gestalt produced in
the subject.
• Subject: System which can adopt potential changes
• Object: what remains stable (in front of the subject)
causing the changes in the subject ~ Model
• Time: Running of the procedure (i.e. change of the
subject). Past: actual; Future: potential
• O. vs S.: In strict sense, both sides change during the
process (O. & S. are only relative regarding the
corresponding change)

I.1 Evolution of the information concept
(a) Plato vs. Aristotle
Plato (idealistic tradition)
• Form is what exists in the first place and it is out of the
world, otherworldliness (a-spatial, a-temporal).
• Forms are participated by appearances (phenomena) and
souls. By these means the observer can really recognize
the forms.
• The innate ideas must be awaken (the observer
recognizes what already was in his soul).
• The observer returns to the truths, slept within himself.

Plato: World of forms
17
Ideas
Form Appearance
I
Decontextualizing:
Die existing Forms belong
to the otherworldliness (a-
spatial, a-temporal)
Observer

Plato and Signal Theory
• From the viewpoint of the modern signal
theory (Digital Transmission): Ideal of
transparence
18
Si
{S1, S2,… SN}
Noise
Si’ Compared with
{S1, S2,… SN}
Si

(b) Aristotle
• Form: embrace the essential properties of a
thing
• Matter: embrace the potential changes
• Every thing has its own form, its own essence,
which correspond to its being.
• The reality of a thing relates to its details, its
differences (dish in Plato and Aristotle)
• There is a general being, which corresponds to
the being of the species. One can inductively
recognize them by observation.

(c) Information concept (Middle ages)
20
Augustine of Hippo (IV c.): „Credo ut intellego“
Anselm (XIc.): „Fidens quarens intellectum“
endeavor towards understanding
Aquinas (XIIIc.): Reality is understandable
Hermeneutic: Interpretation Activity, Imagination Ability
God Belief
RevelationTruth
Requirement:
Noiseless
channels

(d) Information concept
(Modernity)
• Reformation and Enlightenment (XV-XVIII c.) received
the clarity and transparence of Augustine (transparency
≈ unmediated, no distance)
• Physics (XVII c.-) of that time (until 19.Century) had
control over space, but not over time:
“Absolute, true, and mathematical time, of itself, and from its own
nature, flows equably without relation to anything external.”
(Newton, Scholia to the definitions in PN-Principia Mathematica, Bk. 1, 1689)
• Time was left free to philosophy, where it was not
considered as an independent concept, but as something
inherent to processes (Leibniz, Kant, Heidegger,
Bergson).

Ancient Telecommunication
22
Polybios (2nd Century BC)
Hellenic optical telegraphy
(Tower system)
Sextus Julius Africanus (3rd C. AD)
Roman optical telegraphy
(Tower system)

(e) Modern Telecommunication
• The most important difference between early
and modern telecommunication (since XIX c.)
concerns transmission speed.
• Until end of the XIXth c. Information-
Transmission was understood as an immediate
event:
– The time of the transmission process disappears.
– The mediating space correspondingly disappears,
– One can only speak of the process of the E. and R.,
which must be synchronized.

(f) XIX C. Physics
• Late 19th Century Physics (e.g. Maxwell)
understood the being of time as attached
to processes:
– Entropy represents the irreversibility of
processes (Time: inevitable and
unidirectional run of the processes)
– Physics of fields understood Processes in
Space & Time > Change in the understanding
of EM transmission

(g) Mathematical Theory of
Communication (Shannon)
25
Emitter Coder ReceptorDecoder
Original
message Codified
Message
Decoded
message
Noise
Channel
Noiseless Channels
(magische Kanale)
This viewpoint (and alongside the oblivion of space) have many consequences in
the actual game of the globalization:
1. It technically enables the run of the economical processes at the international
level.
2. It technically enables the hiding of power relations.
3. Instead of facilitating social achievements, the power constellation (economical
domination) can easily reconfigure the network of economic agency.

(h) Computer technique and
Cybernetics, 20th C.
26
1940s Pioneering work of Alan TURING, J. VON NEUMANN
1950s Machine-model of neuronal systems (McCULLOCH et al.):
Connectionism
40s-60s First Cybernetics (N. WIENER, R. ASHBY) and System Theory
(L. von BERTALANFFY, CHURCHMANN…)
60s-70s Artificial intelligence (NEWELL, SIMON, MINSKY): Symbol
Processing (e.g. LISP) > MACKAY
60s-80s Codification and Pattern recognition (KOLMOGOROV,
SOLOMONOFF, CHAITIN): Theory of complexity and
Algorithmic Information Theory
1970s- Second Cybernetics (MATURANA, VARELA, van FOSTER)
and complexity theory (PRIAGOGINE, MORIN, ZIMMERMANN)

I.2 Aspects of a general
understanding of information
• Semiotic: Theory of signs and symbols (Morris, 1938)
– The Syntax concerns the occurrence of individual information
units and their mutual relations.
– The Semantic concerns the meaning of information units and
their mutual relations.
– The Pragmatic concerns the effect of information units and
their mutual relations.
A complete understanding of information unfolds in the
dimensions: Syntax, Semantic and Pragmatic

I.2 Aspects of a general
understanding of information
• Timely aspects of information (Weizsäcker):
– Actual: already present and effected information
– Potential: the possibility to obtain actual information.
Namely, the difference between past and future is grasped by
the information concept.
Actual information exists factually, whereas potential
information exists only in relation to possibilities.
Therefore Actual Information can be regarded ontologically,
whereas Potential Information is intrinsically relational.

(I.2.a) Example: information measurement
through unveiling a card
29
32 Cards: 8 cards / type (clubs, spades, hearts and diamonds)
1-8 Clubs 1-8 Spades 1-8 Hearts 1-8 Diamonds
Mínimal # of questions –in average- for yes/no answers
Q1: Black?
A1: No
Q2: Heart ?
A2: No
Q3: > 4?
A3: No
Q4: > 2?
A4: Yes
Q5: 4?
A5: Yes

I.2(a) Syntax and Probability
I = ld (N=No. choices) = - ld (1/N) = - ld p = - log2 p
Extensive measure:
I-Content of a dual system: I(cont) = I(1) + I(2)
• Probability & potential syntactic information
are equivalent concepts for the quantification
of possibilities.
• The concept of probability can be regarded as
a sub-concept of a general information
concept.

I.2(b) Semantic and Pragmatic
• The necessary entanglement of semantic and pragmatic
aspects of information within semantic-pragmatics
offers the possibility to an objectification of semantics.
• Context always presuppose context, Inf. always
presuppose Inf.
• Information exists only relative with respect to a
difference between 2 semantic levels.
• The philosophical key issues in the research of the I-
concept concern the epistemological and ontological
aspects. Both questions are actually interdependent.

I.3 Telecommunication
Information theory
• Shannon’s Information-Entropy
Ii = - log2(pi)
P={1/2, 1/4, 1/8, 1/8 }; Dice
p1=p; p2=(1-p)
• Codification theory
In order to transmit the maximal amount of
information content in the minimal time:
Redundancy-free Source (Morse, 4 symbols ex.)
Huffman method: Lk~Ik

I.3. Telecommunication
Information theory
• Firstness (Erstmäligkeit) and Confirmation
“The word information, in this theory, is used in a special sense
that must not be confused with its ordinary usage. In particular,
information must not be confused with meaning… In fact, two
messages, one of which is heavily loaded with meaning and the
other of which is pure nonsense, can be exactly equivalent, from
the present viewpoint, as regards information... In the theory of
communication, information relates no so much to what is said but
to what could be said. information is a measure of the freedom of
choice communicators have when they select a message.” (Weaver)
The telecommunication I-Theory treats Information
under syntactical aspects

I.3 Telecommunication
Information theory
Is there information without confirmation?
– Phenomenon, manifestation  underlying reality
– Perception, stating that something is the case requires
confirmation
– A confirmed phenomenon provides no information
34
Information
Confirmation (Redundancy)
Firstness (Novelty)
0 11/2
1 0
Shannon (MTC)
Pragmatic-semantics

I.4 Semantical approach to
Information
GDI (data + meaning)
σ is an instance of information (understood as semantic information)
if and only if
1) σ consists of n data, for n≥1
2) The data are well formed
3) The wellformed data are meaningful
Dd datum
x being distinct from y, where x and y are two uninterpreted
variables and the relation of being distinct as well as the domain
are left open to further interpretation.

I.4 Semantic approach to
Information
Environmental information
2 systems a & b coupled in such a way that a’s being F is correlated
to b being G, then carrying the information for the observer of a the
Information that b is G.
Factual semantic information
p qualifies as factual semantic information if and only if p is
(constituited by) well-formed, meaningful and veridical data

I.4 Algorithmic Information
Theory
• The algorithmic information content is a measure of
the syntactical diversity or complexity
• The very shortest description: Ialg(s)=L(pmins)
• Differences with the shannonian concept:
1. Syntactic vs. Minimal complexity as usage of that semantic providing
a minimal syntactic effort.
2. Potential vs. Actual Information
3. Objective vs. Relative quantitative concept: Complexity in relation
to regularities that are readable from a selected semantic space.
• The algorithmic I-content measures actual I. under both
syntactic and semantic aspects. It represents no absolute
quantity but a relative one.
• It is not computable, i.e. it is related to subjects.

I.5 The information concept in
the sciences
• System theory (Bertalanffy, Wiener)
• S.S. (Luhmann), B.S. (Maturana u. Varela)
• Th. of open systems (Weizsäcker)
• Linguistics (Chomsky, Eco)
• Economy (N. Georgercu-Roegen)

the sciences

the sciences
40
Objective or subjective?
Ontological category
independent
Relational
concept,
dependent on:
Subjective
concept
GeneralAbstract Human
Subjectivity or Intencionality
Theory of
Objective
Information
Stonier
Gitt
Ciber-
netics
Wiener
Günther
Algorithmic
Information
Theory
Solomonoff
Kolmogorov
Chaitin
Structure
and process
Structure and
behaviour,
Evolution
Unified
Theory of
Information
Hoffkirchner
Fleissner
Fenzl
Lazlo
Brier (Cibersemiotics)
Release
mechanism
Karpatschof
(Activity
Theory)
Measu-
rement
General
Theory of
Measure
ment
v. Neuman
Brillouin
Mähler
MTC
Shannon
Weaber
Uncertainty,
probability
Interpretable
and
generating
Objecti-
vised
Seman-
tics
Weizsäcker
Lyre (Quantic T. of Inf.)
Matsuno (Diacronic I.)
Biology
Maturana, Varela
2nd O. Cibernetics
V. Foerster
Cognitive
Dretske
mental Difference
Flückiger
Selfreferent. Sist T.
Luhmann
Cognitive Science
Semantic
Theories of
Information
Bar-Hillel & Carnap
Situational
Barwise, Perry,
Seligman, Israel
Truthfulness
Floridi
Dependent of
Relevance
Decision T.
Racionality T.
Inf. Hermeneutics
Capurro
Intersubj. Knowledge
Oeser

41
Syntactical
How is it expressed?
MTC (Shannon,
Weaver)
Semantic
What does it represent? Is it true?
Pragmatic
What value does it have?
Quantum Theory of Information
and Measurement (Lyre,
Mahler…)
Holographic Universe
(Bekenstein)
Syntactical
How is it expressed?
Logical empiricism (Bar-Hillel,
Carnap)
Cognitive constructivism
(Dretske)
Situational semantics (Barwise, Perry,
Seligman…)
Algorithmic Information Theory (Solomonoff, Kolmogorof, Chaitin)
Objectivised semantics (Weizsäcker, Lyre) Theory of Objective Information (Stonier, Gitt)
Unified Theory of Information (Hoffkirchener, Fleissner, Fenzl, Lazlo, Brier,…)
Fuzzy semantics (Zadeh,
Pérez-Amat…)
Theory of Self-referential Systems (Luhmann)
Aesthetic Theory of Information (Bense,
Moles)
Theory of purpose-oriented action (Janich)
Activity Theory (Karpatschof)Activity Theory (Karpatschof)
the sciences

II. Information in the physics
Inf. is still not a physical concept as E, M, S, T 
But may it become a Central concept?
1. Thermodynamics
Principles (1., 2., 3.)
2. Field theory
Appearance and Perception
3. Quantum theory
Measurement theory
4. Space-time Theory
Relativity theory, Quantum Gravity

II.1 Thermodynamics
1. Entropy and 2nd Principle
– (1., 2., 3.) Principles
dS = Qrev/T, dS  0   Qirr irreversible Processes
– BOLTZMANN, MAXWELL, GIBBS: phenomenologic-
macroscopic Th. microscopic-mechanical
– BOLTZMANN (1896): Entropy as quantitative concept:
S = –kBlnp  S = –kBpilnpi
Information entropy and thermodynamic entropy are formal
identical. Both quantities are equal, if one considers Entropy as
potential Information, as quantity of the number of possible micro-
states in a macro-state.

II.1 Thermodynamics
2. Maxwell’s Daemon
44
The molecules have the same
average speed
different average speed

II.2 Field theory (natural limits of information)
45
φύσις κρύπτεσθαι φιλεῖ
«Nature loves to hide»
Heraclitus of Ephesus
S
Observed reality
(Object)
Observer
(Subject)
D
Bounding surface
Arbitrary
complexity
   
2
2
2
2 ,1
,
t
t
v
t



rΨ
rΨ
Structure of the phenomenon

46




































  
),,,,(
),,,,(
wo
11
11
11
nnnMM
nnn
n
N
n
n
N
n
MM zyxvuG
zyxvuG
 ψψΨ fTnn ff


Phenomena (manifestation)
Wavefunction
Complexity of the phenomenon (manifestation)? =
Conveyed information?
1) The details are regularly distributed (~λ/2)
2) The highest gathered information does not depend
on the accuracy of the observation but on the
dimension of the ψ ( a2)
3) There’s only a univocal solution for a discrete
projection over a given bounding surface.
Bounding surface
(Huygens Principle)
Source:
(Real or predicted equivalent)

47
z
x y
a
Observation domain
Domain of
prediction

E

E

Domain of prediction
  OBS
OBS
d Ψ
Ψ
,min/
][
Projection
1
Projection
fT
TTTf
f

 
Domain of observation
Arbitrary
structure
Polyedron of
projection
1) The field of an arbitrary structure is computed
on an observed domain.
2) From this „observation“ a projection over the
perfect polyhedron is determined.
3) The field of both the original structure and the
projected in the prediction domain are equal.
Uniqueness solution for the selected projection distribution
Trans-Operator: f → ψ

48
Projection-Operator: ψ → s
Trans-Operator: s → ψ

49
It is possible to speak of potential and actual (Weizsäcker)
II.3 Quantum theory (Limits of information)
Zeit

50
(II. Appendix) Perception: Consequences of
the physical limits in the human perception
a) regular hole or irregular coloured
protuberance
b) irregular protuberance or regular
coloured hole
• The preferred perceptions tend to be those corresponding
to the simplest configurations (Ockam’s razor)

51
(II. Appendix) Perception
Examples of ambiguos perception

52
Solution of ambiguities
f
N
, Ψ1
N
... ΨN
N
Initial hypothesis
G2
-1
G1
-1
G2G1
Ob{
k
1Ψ }


},{
1kk
d ss
K{
k
s }Ob{
k
2Ψ } Ob{
k
3Ψ } Ob{
k
NΨ }
G3
-1
G 3
GN
-1
G N
● ● ●
(II. Appendix) Perception

III. Information in Biology
The actual decoding of human genome brings in
biology the information theoretical aspects to the
fore
1. Genetics
Theory of heritage, Molecular-biology
2. Evolution theory
Appearance and Perception

III.0 Historical remarks
Darwin: “tiny germs” / mutations
 Galton: „lineages“ (used in ontogenesis)
Mendel (1856): a carrier for every individual
character
 Correns, Tschermark, and de Vries
rediscover the heritage theory, Molecular biology
Miescher (1869): nucleotide of cell kernel (DNA).
Müller (1925, Mutations of Drosophila)
Bateson: “Genetics“, Johannensen: “Gen“

III.0 Historical remarks
Avery (1944): Transformations as f(DNA)
 Hershey and Chase: experiment with bacteriophagus
Schrödiger (1944): „a-periodical crystal“
Watson and Crick: Nature of the DNA Molecule
Not the chemistry of the DNA but the molecular structure:
Information theoretical paradigm

III.1 Genetics
• Central dogma of the molecular biology
• 4 Bases:
(A) Adenine, (G) Guanine, (T) Thymine, (C) Cytosine
• Chargaff’s rules: {A & T}, {G & C} equivalent molar amounts
The DNA heritage-molecule represents in its nucleotide-
structure a genetic code –i.e. syntactical information- for the
production of RNA and Proteins.
56
DNA RNA Polypeptid
Transcription Translation
Since discovery
of Retrovieren
Replication

IV. Information throughout the ladder of
complexity
Progressive Perspective (Emergence)
“The force, through which the development of the
individual occurs, is the same force, through
which different organizations at the earth come
into existence.” (Kielmayer, c. 1790)
Regressive Perspective (computing the origins)
“What we call nature is a poetry enclosed within a
secrete enigmatic writing. If the enigma were
unveiled, we would recognize the spirit’s Odyssey.”
(Schelling, STI, 1800)
57
Purpose:
1. Understanding the emergence of new beings within the world
2. Understanding cosmological and epistemological evolution as
computation

IV. 2. Understanding emergence
Does Emergence exists as something new in nature?
58
• Emergence can be understood as the “real” consequence of
agents’ actions on its own level (Zimmermann & Díaz 2012; Díaz &
Zimmermann 2012, 2013)
• Agents can be generalized by extending S. Kauffman’s idea of
autonomous agency as systems capable to perform
thermodynamic cycles (from pre-geometry, to physics, to chemistry,
to biology, to conscious life, to sociality)
• Ontological irreducibility with respect to the parts constituting the
agency: formation of new classicity, which in turn is related to the
rules of interaction/organization (“new order of existence with its
spatial laws of behavior”, Alexander 1920)

59
• It properly requires rephrasing the philosophical concepts of choice
(from an (un)determined set of possibilities), meaning (related to
the sense of beings, ontological disposition of a real being) and
normalization (as combined effect of a critical mass of interacting
parts) throughout the ladder of complexity.
• The fundamental attributes of Energy, Matter and Information,
Structure need also be reviewed as fundamental elements for the
constitution and evolution of systems.
Potentiality
Energy
Information
Actuality
Matter
Structure
IV. 1. Understanding emergence
Does Emergence exists as something new in nature?

IV.1. Understanding emergence
Does Emergence transcend classical models of computation?
60
• Classical computation model is restricted by Turing’s halting
theorem bzw. Gödel incompleteness (Chaitin), thus it represents a
case of systemic closure, which is indeed needed for the
constitution of an effective agency (for instance, Kuhn’s normal
science). Hence it properly models closure.
• Emergence can be visualized as the need to overcome the
limitations of an algorithmic closure referred to the relations
governing the system, which in turn can be mapped into Turing
machines as long as they are in normal operation.

61
• What computation model can better represent real emergence?
i. Quantum computation (Zizzi 2005)
ii. Cellular automata (Wolfram 2002)
iii. Computational ecologies (Mainzer 2004), etc.
• In the human: perception, scientific discovery, etc. requires
creative abductions which represent a most distant case to
classical computing: epistemological emergences.
• How can we rephrase the relation between physics-aesthetics-
ethics?
Physics
Aesthetics
Ethics
Does Emergence transcend classical models of computation?

Autonomous and fundamental agents
62
We have rephrase the problem in terms of proper agency
1) Generalized Autonomous Agent (S. Kauffman 2000, 2006): system
able to achieve a new closure in a given space of catalytic and work
tasks propagating work out of non-equilibrium states and playing
natural games according to constraints of its environment.
2) For enabling a systematic view of the universe: the fragmented vision
of quantum- and relativistic physics has to be overcome. Thus we set
off from the level of pre-geometry described in terms of spin networks
(R. Penrose) and the related developments of quantum gravity.
• Good candidate: L. Kauffman’s knot theory visualize spin networks as
knots acting on knots to create knots in rich coupled cycles (metabolisms)
• Braunstein-Gosh-Severi (SVR) entropy allows to put forward generalized
conditions of autonomous agency in the sense of S. Kauffman.

Agent’s dynamics
63
3) Agency dynamics: mapped through game theoretical applications (Szabó &
Fáth 2007); Evolutionary system dynamics: mapped through category theory
(Zimmermann 2011). Utilizing the “skeleton-of-the-universe-view”
(Zimmermann 2004), we can set off from the fundamental level of quantum
gravity: inserting steps of a hierarchy of complexity into the functor diagram
from topological quantum field theory:
4) Fundamental attributes of the universe
Potentiality
ENERGY:  to perform work
INFORMATION:  to select/utilize
work in the benefit of the
organization of the system
Actuality
MATTER: actualized (stabilized)
energy
STRUCTURE: actualization of the
organization potential

64
IV.2. Generalizing the concept of information
Generalized 2nd principle of thermodynamics:
entropy/information of a closed system increases
(Potential) information: what the observer ignores about a situation
(Boltzmann) Entropy: what the observer ignores about the
microscopic constitution of a system
Example: steam engine
this is a non-self-organizing
systems working for itself,
but for another system
INFORMATION as potentiality for
building constraints and affordances
that enable propagating work.

65
IV.3. The Progressive Perspective:
From Spin Networks to Social Networks

66
The Odyssey of Autonomous Agency
Step 0: spin networks

67
Step 1: Elementary particles (proton: stable combination of quarks…)
Step 2: Atoms and Molecules

68
Step 3: Starts and Planetary Systems

69
Step 4: Complex molecular structures and living beings (proton channels)

70
INFORMATION as potentiality for building constraints and affordances that
enable propagating work
Step 5: The emergence of seeing (Euglenoid cell)

IV.4. The Regressive Perspective:
Acknowledging the World
71
In Cognitive and social contexts, we deal with agents who have self-
reflection and try to reconstruct objective situations from essentially
limited information (Díaz 2011). Basic level: animal perception.
• We introduce: hermeneutical agency (HA), defined in terms of observation-
interpretation cycles (“sensing reality” – Zubiri).
• The HA can be visualized in thermodynamic terms: abductions as reduction of
(apparent) representation complexity (neg-entropy) or increase in the
probability of interpretation with respect to given constraints (maximal
likelihood). Semantics as interpretation tools, which evolves from the very
sense of the being (means to reproducing itself, and to evolving); from
objective- to reflective- response.
• Semantics are only relatively closed. Openness becomes clear when an
epistemic emergence is needed, rooted on ontological constraints (Levy-
Strauss).

The problem of seeing

73
Animal vision
Additional constraints of vertebrate vision:

74
a) b)
Animal vision

Physical limits of seeing
75
Hence, seeing is necessarily Hermeneutical
• We need sensing reality (information/data)
• We need organising sensing (theories/computing)

76
Hermeneutical agency (computational mapping)
s
N
, Ψ1
N
... ΨN
N
Initial hypothesis
G2
-1
G1
-1
G2G1
Ob{ k
1Ψ }


},{
1kk
d ss
K{ k
s }Ob{ k
2Ψ } Ob{ k
3Ψ } Ob{ k
NΨ }
G3
-1
G 3
GN
-1
G N
● ● ●
Application of
observations
(corresponding to
manifestation of
modality 1, 2,.. )
Gi : allows to derive the
manifestation of modality i from an
interpretation of the object, s.
Gi -1
: allows to make an
interpretation of the object s
consistent with observation i
Truthfulness criterion
Iteration
Interpretation output

77
Conclusive remark concerning
Information and Emergence
• By using the given conceptualization of the fundamental attributes
(E, M, I, S) emergence can be mapped from the pre-geometrical
level to the social one;
• It requires at the fundamental level an unified perspective
(quantum gravity)
• The emergence is visualized as consequence of agent’s action at
its own level causing new classicities (space-time, forces,
particles, molecules, organisms, humans, societies), related to the
rules of interaction/organization.
• Hermeneutical agency requires rephrasing the relation between
physics, ethics and aesthetics (normalization, meaning, choice).

General Understanding of Information

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General Understanding of Information