# Emergence and Evolution of Meaning: The General Definition of Information (GDI) Revisiting Program—Part I: The Progressive Perspective: Top-Down

^{1}

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## Abstract

**:**

“The more perfection a thing possesses, the more it acts and the less it suffers, and conversely the more it acts the more perfect it is.”Spinoza, Ethics, V, prop.40

## 1. Introduction

## 2. Fundamental Physics as an Anchor for a General Understanding of Information

## 3. Starting from Floridi’s Viewpoint

#### 3.1. Reviewing Floridi’s Account of Meaning, Data and Information

#### 3.2. Broadening the Frame of Meaning and Information

## 4. Reframing Information Semiotics from Its Physical Roots

#### 4.1. The Standard Approach and Some of Its Consequences

#### 4.2. Semiotics in Biological Contexts: Barbieri’s Approach

#### 4.3. Semiotics in Human Contexts: Meaning in Frank’s Hermeneutics

## 5. Pre-Reflexive and Reflexive Types of Meaning

#### 5.1. Emergence of Complexity: Solving Capurro’s Trilemma

#### 5.2. Dynamics of Meaning: Thom’s Semiotic Approach

^{3}× R (i.e., an open set at a given time), (2) the union of all cones C(x), with X being a point in that space, and the cones lying within the initial set such that they likewise constitute an open set W which is called zone of influence, (3) an open set V in W which contains U in its boundary and some morphogenetic field. The quotient W/V is called bifurcation zone of the chreod. Unfortunately, the difference between a chreod and a morphogenetic field is not always clear-cut in Thom, but the important point is that the latter temporalizes the former such that the time flow becomes irreversible. Following non-mathematical interpretations of this, particularly within the framework of a quite debatable theory proposed by Sheldrake and others, the concept of morphogenetic fields has been utilized for esoteric purposes, to say the least. But the important point for us here, is that in terms of a dynamics of concrete, observable processes, a given morphology is always the outcome of some chreod action induced by a morphogenetic field (in other words: In the observable world, there is not anything which would not actually evolve). Even solid-state objects can be visualized thus as an acting dynamical system, simply depending on the level of discussion one is maintaining. Though this is indeed aligned to the “constructionism” stance defended by Floridi—regarding his method of the Levels of Abstractions [1], Thom’s approach represents a more dynamical stance as to give a proper account of the emergence of observables and meaning.

## 6. Concluding Remark

## Appendix—Agent-Based Meaningful Games as the Foundation of Systems, Spaces and Networks

**1**. Following an idea of Stuart Kauffman’s, we think of agents in the generalized sense as systems which achieve a new kind of closure in a given space of catalytic and work tasks propagating work out of non-equilibrium states and playing natural games according to the constraints of their environment (see note [133]). In particular, (physical) space is visualized then, as being comprised of autocatalytic autonomous Planck scale agents coevolving with each other serving at the same time as some sort of crystallization of seeds of classicity (in the physical sense). This co-evolution is taking place according to what Kauffman calls 4th Law of Thermodynamics: The maximum growth of the adjacent possible in the flow of a non-ergodic Universe maximizes the rate of decoherence and thus the emergence of classicity. There is also a hierarchy of such agents depending on the explicit complexity of those in question (“higher-order agents”) such that human agents in particular (as constituents of social systems) represent a stage of higher complexity as compared to physical, chemical, or biological systems, respectively (games of various types of agents are nicely illustrated by Szabó and Fáth [134]). But on the fundamental level of physics, Kauffman mentions the possibility to visualize spin networks as knots acting on knots to create knots in rich coupled cycles not unlike a metabolism. Hence, they (or their constituents) show up as a sort of “fundamental agents” (see note [135]).

**2**. If we take up the viewpoint of Kauffman’s, then it appears to be straightforward to find the fundamental agents in the loops of loop quantum gravity (and the associated quantum information theory) in the first place: This is so because it is the loops which combine in order to form spin networks. In fact, six of them co-operate in order to produce one hexagon of the network.

_{α}along α defined by (the s

_{i}being points of α)

**3**. Obviously, this bears a strong resemblance to the Wilson loop representation (hence, we think here of a kind of loop transport according to Stuart Kauffman’s idea of agents), and is also essentially a Feynman-type integral which gives the probability for a (physical) system to go from one state to another:

**4**. There is a number of important cross-relationships which connect the notion of loops with the notion of knots: Louis Kauffman’s bracket algebra (the boundary algebra of containers and extainers) turns out to be the precursor of the Temperley-Lieb algebra important in order to construct representations of the Artin braid group related to the Jones polynomial in the theory of knot invariants (Kauffman [113,140], Grand [129], Neuman [141], p. 11, p. 48, pp. 91ff). As the elementary bracket algebra is to biologic what Boolean logic is to classical logic, this has important epistemological consequences [75]. On the other hand, the Jones polynomial can itself be visualized in terms of quantum computers, because a similar partition function of the form Z

_{K}= < cup □ M □ cap > with creation and annihilation operations, respectively,

_{σ}<K□σ>d

^{║σ║}can be related to the process of quantum computation (as can, by the way, the spin network formalism itself). As spin networks are nothing but graphs, the agency in question here is motion on graphs or percolation in networks such that phase transitions can be represented in terms of an appropriate cluster formation of connected components. This is what points to a close relationship to cellular automata utilized for the simulation of evolutionary processes (cf. Conway’s game of life or Wolfram’s approach [142]). Stuart Kauffman has associated this with the emergence of collectively autocatalytic sets of polymers, and in fact with the onset of forming classicity with regards to physics. It is straightforward (in epistemic terms) to generalize this (with a view to higher-order agents) to chemical, biological, and other systems.

**5**. But there is still another point to that: In the approach of Barrett and Crane [143,144], the idea is to generalize topological state sum models in passing from three to four dimensions by replacing the characteristic SO(3) group with SO(4), or its appropriate spin covering, SU(2) × SU(2), respectively. The concept of spin networks is also generalized then, by introducing graphs with edges labeled by non-negative real numbers (called “relativistic spin networks”). Applying this kind of “spin foam” model to Lorentzian state sums demonstrates their finiteness in turn implying a number of choices made from physical and/or geometrical arguments [145]. The really interesting aspect of this is its relation to the group SL(2,C): because this is the double cover of SO(3,1) and the complexification of SU(2) which in turn is the double cover of SO(3). On the other hand, SL(2,C) is the group of linear transformations of C

^{2}that preserve the volume form. Thanks to an e-mail crash course on these matters referring to the Barrett-Crane model and made available online by John Baez and Dan Christensen [146], where they use the terminology of the former’s quantum gravity seminar [147], it is easy to understand that constructions in the sense of Barrett-Crane turn out to be invariant under SL(2,C). In other words, we essentially deal with states in C

^{2}which are spinors. And it is from quantum theory and special relativity that we know about their relevance. On the other hand, as Baez notes [146], and as we will see shortly, a state in C

^{2}can also be called a qubit. So “[w]hat we [a]re really doing, from the latter viewpoint, is writing down‚ quantum logic gates’ which manipulate qubits in an SU(2)-invariant [in fact, SL(2,C)-invariant] way. We [a]re seeing how to build little Lorentz-invariant quantum computers. From this viewpoint, what the Barrett-Crane model does is to build a theory of quantum gravity out of these little Planck-scale quantum computers”. This is obviously very much on line with the arguments of Zizzi, Lloyd and others. Moreover, it is referring to the explicit level of spin networks: That is, the aforementioned “boundary layer” between the physical world and its foundation shows up as a “shift of quantum computing” processing the fundamental information necessary for performing the transition from foundation to world (or in other words: For actually producing a world out of its foundation).

**6**. Utilizing the “skeleton-of-the-universe view” [59,148], the idea would be to insert various steps of a hierarchy of complexity in the overall functor diagram from topological quantum field theory (cf. [149]):

- (a) to show that loops are fundamental agents in that their loop motion (their self-assembly and combination into spin networks) corresponds to Stuart Kauffman’s definition of agents. Outline of Proof: From recent work of Donnelly’s [150] we know that the appropriate entropy is the von Neumann entropy of the form S(ρ) = tr(ρ ln ρ), where ρ is a suitable density matrix. In Kitaev and Preskill [151] as well as Rovelli and Vidotto [152] we find that for spin networks in loop quantum gravity, it is especially the Braunstein-Ghosh-Severini (BGS) entropy which is relevant here: This refers essentially to a quantum field theory on a space Ω ⊆ ∑ with
_{ ∑ }=_{Ω}_{Ω}^{C}as adequate tensor product of the associated Hilbert spaces such that . In particular, for the loops of this theory, the appropriate Hilbert spaces are defined by the cyclic functions of an SU(2) connection A. Hence: {ψ; ψ(A) = f(U(A, γ_{1})…U(A, γ_{L}))}, where is a spin network state. The density matrix of the underlying graph Γ turns out as the Laplacian matrix L(Γ) (essentially the difference between degree matrix and adjacency matrix) divided by the degree-sum of such graph. Then, ∮_{γ}dS_{E}(Ω) ≥ 0 fulfills Stuart Kauffman’s condition for an autonomous agent. - (b) to actually describe what the mapping em looks like in detail.
- (c) to introduce intermediate stages of hierarchy into that mapping.

**7**. However, while talking about all of that, we notice that this is the outcome of the modeling procedure. In other words, the systematic approach outlined above is itself a model, i.e., a mapping of the world, not the world itself. We utilize the concepts of space, network, and system according to our epistemological principles: As such networks serve as a formal skeleton for a space and for a system, respectively, while they are graphical representations of both of them. The concept of space serves also the graphical representation of what we call a system. The system is the concept we have of what we are able to observe in concrete terms. But what we observe is only part of the world (our ontological directive is: The world is not as we observe it). But we are products of that world ourselves. Hence, there is the necessity of a cognitive metatheory for our other theories which tells us something about the basic limitations of our possible knowledge. This entails the necessity of a self-loop: Humans model the world by inventing theories according to the cognitive constraints this same world is imposing upon humans. Theories constitute categories of meaning. If humans show up then as communities of communities of fundamental (natural) agents, they are, with respect to the latter, emergent structures in nature. And so are all of their reflexive concepts. Hence, the concept of (human) meaning itself is emergent with respect to fundamental proto-meaning defined in terms of the directed behaviour of fundamental agents. This may be utilized as a grounding of the concepts of pre-reflexive and reflexive meaning, respectively. (For „reflexive mentation“ see also Jantsch [40], p. 237, and as early as 1748 La Mettrie [154]; cf. Grand [129], p. 6) Hence, the Universe is meaningful from the outset, but it is only humans who develop reflexive meaning such that they actually know that there is meaning.

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Zimmermann, R.E.; Díaz Nafría, J.M. Emergence and Evolution of Meaning: The General Definition of Information (GDI) Revisiting Program—Part I: The Progressive Perspective: Top-Down. *Information* **2012**, *3*, 472-503.
https://doi.org/10.3390/info3030472

**AMA Style**

Zimmermann RE, Díaz Nafría JM. Emergence and Evolution of Meaning: The General Definition of Information (GDI) Revisiting Program—Part I: The Progressive Perspective: Top-Down. *Information*. 2012; 3(3):472-503.
https://doi.org/10.3390/info3030472

**Chicago/Turabian Style**

Zimmermann, Rainer E., and José M. Díaz Nafría. 2012. "Emergence and Evolution of Meaning: The General Definition of Information (GDI) Revisiting Program—Part I: The Progressive Perspective: Top-Down" *Information* 3, no. 3: 472-503.
https://doi.org/10.3390/info3030472