The Cybersemiotics and Info-Computationalist Research Programmes as Platforms for Knowledge Production in Organisms and Machines
1. Cybersemiotics and Info-Computationalism
(W)e must do more than include physics, chemistry, and biology with their functional explanations into our definition of science: we need to embrace a Peircian biosemiotic interpretation of biology. Cybersemiotics combines this with a theory of levels, information, semiotics, and language interactions. This means that we do not dismiss the results obtained so far, but rather that we relativise their implicit frameworks and integrate the science into a new framework while adding semiotics.Brier  p. 431.
The cybernetic computational informative view is based on universal and abstract (un-embodied) conceptions of information and computation that is the foundation of “the information processing paradigm”, which is foundational for much cognitive science and its latest developments into brain function and linguistics comprising also a philosophy of science. It is claiming that “information” is the objective forms of the world. That it can be objectively parted into pieces of “data” and that humans, brains, computers and organizations process them in the basic same way, which is called “computation” and is a basic – not really well-defined concept—of information processing that goes beyond the Turing computer definition. Anyway it is a “software” definition opposed to a “hardware” definition (metaphors again).Brier .
A preferable alternative is provided by an informational approach to structural realism, according to which knowledge of the world is knowledge of its structures. The most reasonable ontological commitment turns out to be in favour of an interpretation of reality as the totality of structures dynamically interacting with each other.Floridi  p. 151.
The relation of difference seems a precondition for any other relation and hence for any process of knowledge. Relata as merely differentiated entities and nothing else (at least not yet) are possible only because there is a relation of initial, ontological difference in the first place.Floridi  p. 234.
A significant consequence of ISR is that, as far as we can tell, the ultimate nature of reality is informational, that is, it makes sense to adopt Levels of Abstraction that commit our theories to a view of reality as mind-independent and constituted by structural objects that are neither substantial nor material (they might well be, but we have no need to suppose them to be so) but cohering clusters of data (not in the alphanumeric sense of the word, but in an equally common sense of differences de re, i.e., mind-independent, concrete, relational points of lack of uniformity). Structural objects work epistemologically like constraining affordances: they allow or invite certain constructs (they are affordances for the information systems).[ibid 154]
Coming back to the main discussion, we may observe that computation seems to be everywhere but what is it precisely? A common way to tell a computation is by what Aristotle would have called its `efficient cause' what today we'd call its proximate mechanisms.
And how about the entire universe, can it be considered to be a computer? Yes, it certainly can, it is constantly computing its future state from its current state, it's constantly computing its own time-evolution! And as I believe Tom Toffoli pointed out, actual computers like your PC just hitch a ride on this universal computation!
2. Info-Computational Naturalism and Knowledge Generation
In the history of physics, we have learned that there are distinctions that we really should not make, such as between space and time… It could very well be that the distinction we make between information and reality is wrong. This is not saying that everything is just information. But it is saying that we need a new concept that encompasses or includes both.
3. Information and Computation in Biological and Intelligent Artificial Systems
If we take a dead bird and throw it up into the air its path describes parabola, in conformity with the laws of motion (…). Take a living bird and throw it up in the air and something entirely different happens. Fundamentally, it is matter of understanding how, given a physical universe dominated by matter and energy, systems can emerge that determine their own behavior by means of information or computation.Emmeche .
4. Knowledge Generation as Natural Computation
5. Info-computational Framework for Evolution of Embodied Knowledge
But this is just to say that any conception of animal behavior which makes sense of it all will have to see the animal’s cognitive equipment as serving the goal of picking up and processing information. And this commits one to the notion of animal knowledge.Kornblith .
any evolving population 'learns' about its environment, in Harms' sense, even if the population is composed of organisms that lack minds entirely, hence lack the ability to have representations of the external world at all.
An autopoietic machine is a machine organized (defined as a unity) as a network of processes of production (transformation and destruction) of components which: (i) through their interactions and transformations continuously regenerate and realize the network of processes (relations) that produced them; and (ii) constitute it (the machine) as a concrete unity in space in which they (the components) exist by specifying the topological domain of its realization as such a network.
6. Interaction of an Agent with the Environment and Info-computational Evolution
This circularity, this connection between action and experience, this inseparability between a particular way of being and how the world appears to us, tells us that every act of knowing brings forth a world … all doing is knowing, and all knowing is doing.Maturana and Varela , p.26.
Every interaction of an organism, every behavior observed, can be assessed by an observer as a cognitive act. In the same way, the fact of living—of conserving structural coupling uninterruptedly as a living being—is to know in the realm of existence. In a nutshell: to live is to know (living is effective action in existence as a living being).”. p. 174.
7. Why Our Perception of the World is an Illusion and What Can We Learn From It?
Hence the brain does not directly map the external world. From this proposition follows the notion of “interpreting brain”, i.e. the notion that the brain must interpret symbols generated by itself even at the lowest level of information processing. It seems that many problems related to information processing and meaning in the brain are rooted in the problems of the mechanisms of symbol generation and meaning.Kaneko and Tsuda.  p. 192.
8. Observing the Observer Observing Observer and Beyond. Self-reflective Knowledge
- Knowledge is not passively received either through the senses or by way of communication, but is actively built up by the cognizing subject.
- The function of cognition is adaptive and serves the subject's organization of the experiential world, not the discovery of an ‘objective ontological reality’.
The key question that arises in this ‘constructive’ approach lies in the relationship between the virtual world (the model) and reality. The virtual world should not just be an imitation of reality, but a sort of abstraction from reality, and be constructed from our side by utilizing some abstracted essential features of reality. Understanding the relationship between the virtual world and reality is a fundamental issue in the study of complex systems with a constructive approach. Obviously, a virtual world must have some interface with reality.
There is an external world … but we have no direct contact with it. p. 64.
And I think this is the idea which goes beyond the assumption that relativism is simply arbitrary: every observation has to be made by an observing system, by one and not the other, but if systems are in communication, then something emerges which is not arbitrary anymore but depends on its own history, on its own memory.Luhmann in Rasch and Wolfe 
Cognition deals with an external world that remains unknown and has to, as a result, come to see that it cannot see what it cannot see.Luhmann  p. 65
(…) the representation in itself does not produce the object insofar as its existence is concerned, for we are not here speaking of causality by means of the will. None the less the representation is a priori determinant of the object if it is to be the case that only through the representation is it possible to know the object.Kant  B 124–125.
9. What can be Seen Looking "From Within" and Looking “From Without”?
The ultimate purpose of science is to reconstruct a world by clarifying a modality of motion and structure. It is also possible to express virtual worlds and to hopefully synthesize them via mathematics and computers. The latter makes it possible for the former to appear in the world. By this act, scientists try to answer the question ‘what is reality?’.Tsuda and Ikegami 
10. Two Paradigmatic Projects: The Blue Brain Project and The Biosemiotic Study of Genes, Information and Semiosis. Relevance of Info-computationalist Thinking for Scientific Modeling
and:Today, a number of researchers consider information talk as inadequate and ‘just metaphorical’, expressing a skepticism about the use of the term ‘information’ and its derivatives in biology as a natural science. We disagree with this position, claiming instead that the notion of information and other related ideas grasp some fundamental features of biological systems and processes that might be otherwise neglected. Our problem is not to get rid of information talk, but rather to clarify it by using a proper theoretical framework. We intend to show that the use of semiotic concepts and theories to interpret information talk can contribute to the construction of a precise and coherent account of information in biology. For this purpose, we introduce here a model of information as semiosis, grounded on Peircean semiotics.
This model is consistent with the best scientific understanding and yet non-reductionist, integrating notions of signs, molecules, and natural interpretation in the tradition of the general semiotics, or the sign theory of Charles Sanders Peirce. It offers a new solution to how to understand and define “gene” in biology, and it develops a profound proposal for another concept of information that does not reduce information to digital bits of computation, but sees it as closely related to natural forms and processes, as the ones known from living organisms.
Bohr’s views can be roughly summarized as follows: Communicable sets of interpreted perceptions are data. Communicable sets of interpreted data are information. Communicable sets of interpreted information are knowledge. Theoretical and contextual issues are involved at every step – but different theories are often involved at the different levels.McEvoy .
I hope that this simple example is sufficient to suggest to you the possibility of generalizing this principle in the sense that “computation” can be seen on at least two levels, namely, (a) the operations actually performed, and (b) the organization of these operations represented here by the structure of the nerve net. In computer language (a) would again be associated with .operations, but (b) with the .program. As we shall see later, in “biological computers” the programs themselves may be computed on. This leads to the concepts of “meta-programs”, “meta-meta-programs”, . . . etc. This, of course, is the consequence of the inherent recursive organization of those systems.
Chemical processes and structures can describe and explain crucial aspects of the physiological structure as well as the processes of the nervous system that are necessary for first-person experiences, but chemistry cannot describe the experience as such.Brier 
In the classical view of science, through the mechanism of inter-subjectivity and the requirement of reproducibility of results, specific subjective components in a researcher’s experience of the world are washed out from scientific accounts. First order accounts are for obvious reasons important in the fields like medicine, psychology, psychiatry and neuroscience, where they help the construction of a new knowledge about the relationships between the human mind and body. Scientific methods allow for diversity in the context of scientific discovery where among others first order accounts can be applied, while according to Reichenbach in the context of justification there are strict rules of logic and inter-subjectivity that will establish if the hypothesis should be accepted or not. The scientist in general is not a part of the story of science. In a big research projects like Blue Brain this is a blessing, as having every researcher’s personal account from within his or her total experience of the world would be extremely complex even if handled by the most powerful supercomputers.A) The “first-person account” is included as a “third-person account” of a “first-person account”.
Our idea of knowledge is gradually changing, as we learn about the mechanisms of knowledge production. This process which we already may notice in practice concerns even the evolution of the understanding of science – what science is and how it may develop in the future. Dodig Crnkovic  addresses the phenomenon of computing sciences becoming more and more the contemporary ideal of science and thus replacing physics which through the centuries epitomized the ideal of science. Computing sciences/Informatics differ from the classical idea of scientific research in their having human/user/agent in the center of interest. This informational agent is part of the info-computational universe. Inter-disciplinary, cross disciplinary and trans-disciplinary approaches are characteristics of this framework. For Galileo the Great Book of Nature was written in the language of Mathematics. For us today the reality is info-computational and the nature is a computational network best studied by computer simulation combined with direct investigations in the physical world (Fredkin, Chaitin, Wolfram, Lloyd). The information and computation are present in all sciences and other scholar fields, as well as in arts and culture in general. Communication (information exchange) is becoming global and plays an increasingly important role in knowledge production. The boundaries of new knowledge production fields are more fluid and fields mix easily, influencing and reinforcing each other, forming new branches such as cognitive robotics, artificially intelligent environments and simulated virtual worlds. From this development the new insights are expected in the nature of knowledge and its relationships to agency and intentionality.B) A transdisciplinary mixture of different knowledge-production cultures will bring in “knowledge from within” into traditionally externalist fields with new emerging disciplines as a result.
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Dodig Crnkovic, G. The Cybersemiotics and Info-Computationalist Research Programmes as Platforms for Knowledge Production in Organisms and Machines. Entropy 2010, 12, 878-901. https://doi.org/10.3390/e12040878
Dodig Crnkovic G. The Cybersemiotics and Info-Computationalist Research Programmes as Platforms for Knowledge Production in Organisms and Machines. Entropy. 2010; 12(4):878-901. https://doi.org/10.3390/e12040878Chicago/Turabian Style
Dodig Crnkovic, Gordana. 2010. "The Cybersemiotics and Info-Computationalist Research Programmes as Platforms for Knowledge Production in Organisms and Machines" Entropy 12, no. 4: 878-901. https://doi.org/10.3390/e12040878