Dear colleagues,

Even though I agree with all Jeremy writes in his new post, I would still 
return back to the opposite side (where Pedro’s previous post left us) and try 
to think about the big picture.
I am sure there will be many FISers who will take the challenge of discussing 
the details of construction of an autogen as a bridge between meaning and 

In his first post, Jeremy wrote:

“Terry and the Pirates have a long standing rule: One cannot employ as 
explanation that which hasn't yet been explained. Failing to hold this standard 
opens researchers up to merely taxonomical work, positing forces, properties 
and capacities defined solely by their consequences, in effect mistaking 
questions as answers. Hence, our focus on exploring reference at its earliest 
possible emergence, and explaining exactly how that emergence occurs, since 
emergence is also a question, not an answer, an explanandum not an explanans.”

“We Pirates do what we can to stay on the epistemological methodist side of 
Epistemological methodism is explained as the opposite of epistemological 
particularism, which is the belief that one can know something without knowing 
how one knows that thing. So according to epistemological Methodists, for me to 
know implies not only that I know that I know but even that I know how I know. 
It is a very strong assumption.

It seems to me to exclude constructive approaches to knowledge generation. When 
we construct, we simply use elements that suit the purpose of construction. 
There is no very hard requirement to understand bricks. How do we conceptualize 
knowledge and knowing? What does it mean “to know” and “to know that we know”? 
How detailed, precise and formal knowledge should be for me to claim “I know”?
For example I can say: we know that the universe consists of matter/energy in 
space/time. But how much indeed do we know about it? Only a small fraction 
(<5%?) of the content of the universe seems to be made of matter/energy while 
the majority of the universe is made of dark matter/dark energy and at the 
moment we do not know what they are. This sounds like a very pessimistic view 
of our present knowledge. However I strongly believe that this state must be 
temporary and that a new break-through will come soon. It may happen in the 
similar way as in the time of Planck, who solved the problem of the ultraviolet 
catastrophe, (a prediction of late 19th century/early 20th century classical 
physics that an ideal black body at thermal equilibrium will emit radiation 
with infinite power). Some assumptions (something that we believe we know and 
we probably even believe that we know why we know) are simply wrong.
Knowledge is a dynamic, nonlinear, adaptive, learning system.
That is why the suggestion to study information not only on the level of 
physics and chemistry in a well-defined simplified system, but on many 
different levels of abstraction is relevant. Some people (Alexej Kurakin for 
example, (Kurakin, 2011)) see fractal structures that govern generation of 
information, from atoms to human societies, and one can learn about the 
properties of one level from the observed patterns on some other levels. The 
reason to look at the fuzzy “big picture” at the same time as we construct much 
more coherent, crispy and convincing detailed aspects of it is that they are 
inseparably connected. The role of unexplained pieces in the theoretical 
framework is as placeholders. Like in lazy evaluation, we do not do anything 
about it until we learn more at some point.

(In programming language theory, lazy evaluation, or call-by-need[1] is an 
evaluation strategy which delays the evaluation of an expression until its 
value is needed (non-strict evaluation) and which also avoids repeated 
evaluations (sharing).[2][3] The sharing can reduce the running time of certain 
functions by an exponential factor over other non-strict evaluation strategies, 
such as call-by-name.

This is not meant as a critique of Terry’s approach, which is fascinating 
elegant, and refreshing among many fuzzy discussions about the nature of 
reference and significance. However, connections and integration with other 
levels and perspectives on information might be instructive and worthwhile, 
especially from Terry who has done so much research on higher levels. Such as 
e.g. in Harrington et al. (2001). “Science, culture, meaning, values: a 
dialogue” Annals of the New York Academy of Sciences. and of course even more 
in Deacon T. (2012) the Incomplete Nature: How Mind Emerged from Matter. Norton 
& Company

What might be interesting on the synthetic side (as the opposite side of the 
analytic one as presented in the New Year’s Essay) would be integration of 
levels that Terry has in the Incomplete Nature, based on the dynamics of 
information, where information has different meaning on different levels of 
abstraction/organisation. In the similar way as an autogen, as a 
self-organizing unit that preserves itself dynamically and grows via a 
combination of autocatalysis and self-assembly, our knowledge grows dynamically 
and the meaning of pieces changes accordingly. In other words, it is not only 
self-organizing but also self-generating. Different scientific domains support 
and regulate each other; different “domain-specific” (or “science-specific”) 
models can help better construction or generation of knowledge of the whole as 
well as of the details. Specifically, it might be useful to connect to 
computing (as information dynamics), as Pedro suggests.

Computing (Rosenbloom, “The Fourth Great Scientific Domain”) seen as 
information dynamics, goes together with the physical, the biological, and the 
social. The project of naturalization proceeds by connecting all four domains. 
(Dodig-Crnkovic, 2014) The attractiveness of the project as Terry’s (as 
presented in the Incomplete Nature) is in its contribution to the 
naturalization of reference and significance – concepts that still are highly 
mystified in the eyes of many.

At the end, I have two questions.

First the particular one. I would like to know what exactly is the difference 
between autogenesis and autopoiesis? It seems to me that autogenesis as it 
looks like from Terry’s Opening Essay is a step before the whole system can be 
integrated and said to be alive. On the other hand autopoiesis is the process 
of life of an organism such as cell with all properties of a living organism. 
Autogen seems to me as a chemical automaton while autopoetic system is alive. 
The theory of autopoiesis is descriptive and qualitative. It does not make the 
insights made by Maturana and Varela less important. Understanding autopoiesis 
as cognition makes a vital connection between mind and matter. Like Pedro, I 
also believe that study of the behavior of prokaryotic cells such as bacteria 
is useful as it can reveal a lot about information processing as social 
cognition (Ben-Jacob, Becker, & Shapira, 2004; Ben-Jacob, Shapira, & Tauber, 
2006, 2011; Ben-Jacob, 2008, 2009a, 2009b) (Ng & Bassler, 2009; Waters & 
Bassler, 2005).

There is a lot we don't know about such complex systems as bacteria but we can 
learn relevant things even if we apply “lazy evaluation” strategy for many 
parts in the model. In other words, it should be possible and reasonable to 
build knowledge even though we do not know (enough) about parts we build from 
and their mutual interactions.

My second question, the general one, goes back to Pedro’s post:  how the New 
Year’s Essay connects to the big picture with four great scientific domains?

With best regards,

Ben-Jacob, E. (2008). Social behavior of bacteria: from physics to complex 
organization. The European Physical Journal B, 65(3), 315–322.
Ben-Jacob, E. (2009a). Bacterial Complexity: More Is Different on All Levels. 
In S. Nakanishi, R. Kageyama, & D. Watanabe (Eds.), Systems Biology- The 
Challenge of Complexity (pp. 25–35). Tokyo Berlin Heidelberg New York: Springer.
Ben-Jacob, E. (2009b). Learning from Bacteria about Natural Information 
Processing. Annals of the New York Academy of Sciences, 1178, 78–90.
Ben-Jacob, E., Becker, I., & Shapira, Y. (2004). Bacteria Linguistic 
Communication and Social Intelligence. Trends in Microbiology, 12(8), 366–372.
Ben-Jacob, E., Shapira, Y., & Tauber, A. I. (2006). Seeking the Foundations of 
Cognition in Bacteria. Physica A, 359, 495–524.
Ben-Jacob, E., Shapira, Y., & Tauber, A. I. (2011). Smart Bacteria. In L. 
Margulis, C. A. Asikainen, & W. E. Krumbein (Eds.), Chimera and Consciousness. 
Evolution of the Sensory Self. Cambridge Boston: MIT Press.
Dodig-Crnkovic, G. (2014). Modeling Life as Cognitive Info-Computation. In A. 
Beckmann, E. Csuhaj-Varjú, & K. Meer (Eds.), Computability in Europe 2014. LNCS 
(pp. 153–162). Berlin Heidelberg: Springer.
Kurakin, A. (2011). The self-organizing fractal theory as a universal discovery 
method: the phenomenon of life. Theoretical Biology and Medical Modelling, 
8(4). Retrieved from
Ng, W.-L., & Bassler, B. L. (2009). Bacterial quorum-sensing network 
architectures. Annual Review of Genetics, 43, 197–222.
Waters, C. M., & Bassler, B. L. (2005). Quorum Sensing: Cell-to-Cell 
Communication in Bacteria. Annual Review of Cell and Developmental Biology, 21, 

From: Jeremy Sherman 
Date: Sunday 18 January 2015 03:41
To: fis <<>>
Subject: Re: [Fis] Fis Digest, Vol 10, Issue 11

It would be satisfying perhaps to think of our collective work as at the 
forefront of the development of what will become A Grand Domain of Science, but 
I would say the better trend in current science is toward careful integration 
between domains rather than toward established grand divisions, which seems a 
more a classical approach. Doesn't information play out in the biological and 
the social domains? Isn't our most ambitious goal here to explain 
scientifically the relationship between information and the physical domain?

Whether modest or foolhardy as Terry suggests or of some other stature, Terry's 
approach addresses the source of the great schism in all academic and 
intellectual circles: Physical scientists are appropriately barred from 
explaining behavior in terms of the value of information for some end-directed 
self about, or representative of anything. But biological and social scientists 
can't help but explain behavior in those terms. Focusing, precisely on possible 
transitions from the physical domain to the living and social domains is 
exactly what a scientific approach demands.

Lacking an explanation for the transition from mechanism to end-directed 
behavior (which is inescapably teleological down to its roots in function or 
adaptation--behaviors of value to a self about its environment), science is 
stuck, siloed into isolated domains without a rationale.

To my mind, this makes the implications of meticulous work at the very border 
between mechanism and end-directed behavior anything but modest in its possible 
implications. In this I agree with Pedro. With what we now know about 
self-organization-- how it is footing on the physical side for a bridge from 
mechanism to end-directed behavior but does not itself provide the bridge,  we 
are perfectly poised to build the bridge itself, through an integrated science 
that explains the ontology of epistemology, providing solid scientific ground 
over the absolutely huge gaping hole in the middle of the broadest reaches of 
scientific and philosophical  endeavor.

Whether Terry's work or someone else's work bridges that gap, I predict that, 
at long last, the gap can and will be finally filled, probably within the next 
decade. As ambitious researchers this would be a lousy time for any of us, 
Terry included, to stick to our guns in the face of substantial critique 
revealing how a theory we embrace merely provides a new, more clever way way to 
hide or smear over the gap pretending it isn't there, which is why I would love 
to see this discussion refocus on the article's detailed content. Though the 
implications of this research at the borderline may be grand, the research, in 
the doing, is as Terry implies as modest any careful scientific work.

Jeremy Sherman

On Sat, Jan 17, 2015 at 5:06 AM, Moisés André Nisenbaum 
<<>> wrote:
Hi, Pedro.
I didnt receive th image (Figure 1. The Four Great Domains of Science)
Would you please send it again?

Thank you.


2015-01-17 9:00 GMT-02:00 
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Today's Topics:

   1. Re: Beginnings and ends---Steps to a theory of reference &
      significance (Pedro C. Marijuan)

---------- Mensagem encaminhada ----------
From: "Pedro C. Marijuan" 
To: "'fis'" <<>>
Date: Fri, 16 Jan 2015 12:43:40 +0100
Subject: Re: [Fis] Beginnings and ends---Steps to a theory of reference & 
Dear Terry and FIS colleagues---and pirates,

Just a brief reflection on the below.

(From Terry's last message)...
So my goal in this case is quite modest, and yet perhaps also a bit
foolhardy. I want to suggest a simplest possible model system to use
as the basis for formalizing the link between physical processes and
semiotic processes. Perhaps someday after considerably elaborating
this analysis it could contribute to issues of the psychology of human
interactions. I hope to recruit some interest into pursuing this goal.

In my view, any research endeavor is also accompanied by some "ultimate" goals 
or ends that go beyond the quite explicit disciplinary ones. In this case, say, 
about the destiny of the constructs that would surround the information concept 
(or the possibility of framing an informational perspective, or a renewed 
information science, or whatever), wouldn't it be interesting discussing in 
extenso what could that ultimate vision?

I mean, most of us may agree in quite many points related to the microphysical 
(& thermodynamic) underpinning of information, as it transpires in the 
exchanges we are having--but where do we want to arrive finally with the 
construction activity? I tend to disagree with localist aims, even though at 
the time being they may look more prudent and parsimonious. Putting it in 
brief, too briefly!, and borrowing from Rosenbloom (P.S. 2013. On Computing: 
The Fourth Great Scientific Domain) the idea is that information science, 
properly developed and linked with computer science and mathematics, should 
constitute one of the Great Domains of contemporary science. The informational 
would go together with the physical, the biological, and the social: 
constituting the four great domains of science. See Figure below. Rather than 
attempting the construction of another average or standard discipline, 
information science is about the making out of one of the “great scientific 
domains” of contemporary knowledge.

More cogent arguments could be elaborated on how to cover sceintifically the 
whole "information world" (human societies, behaving individuals, brain 
organization, cellular processes, biomolecules) and the problem of 
interlocking--crisscrossing a myriad of information flows at all levels. But 
the point is, "ends", although unassailable, may be as much important as 

Thanks in advance for the patience!



Figure 1. The Four Great Domains of Science. The graphic shows the network of 
contemporary disciplines in the background;
while the superimposed “four-leaf clover” represents the four great scientific 

Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
Instituto Aragonés de Ciencias de la Salud
Centro de Investigación Biomédica de Aragón (CIBA)
Avda. San Juan Bosco, 13, planta X
50009 Zaragoza, Spain
Tfno. +34 976 71 3526<tel:%2B34%20976%2071%203526> (& 6818)<>

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Moisés André Nisenbaum
Doutorando IBICT/UFRJ. Professor. Msc.
Instituto Federal do Rio de Janeiro - IFRJ
Campus Maracanã<>

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