Re: Re: [PEIRCE-L] Pragmatics and Peirce

[Jerry Rhee]

Dear Edwina, list,



You said:

“My point is only that there is a lot of work being done now in the actual
world, examining complex information dynamics -

and Peirce's framework, to me, is perfect as an analytic tool for that
purpose.



*I just wish* we could expand the knowledge of this framework –

and *see *how very pragmatic and enlightening it could be.”



To which I would add, we seem to be getting along just fine without it.



And given the constant snipping back and forth that goes on in this list

(for instance, on even what a ‘subject’ is;

I mean, who doesn’t know the difference between subject and predicate?),

why would you recommend something to the community-at-large

a something that you can’t even justify to a list who claims to embrace
Peirce?



That is, when you haven’t been able to persuade a group who say

‘we honor that which you claim is not being used enough’ to take right
action,

why would an outside community ever think they could find any use for it,
whatsoever?



It all seems crazy from my point of view..



With best wishes,

Jerry R

On Mon, Apr 1, 2019 at 1:11 PM Edwina Taborsky <tabor...@primus.ca> wrote:

> Thanks for your comments.
>
> I don't see how anyone could try to say that I am stretching Peirce's
> words, for after all, his framework has to be an analytic structure to DO
> something! It doesn't make any sense to set up, for example, that semiosic
> triad - with its full six nodes - without using it to explain the world.
> And - he does indeed explain it in one such example - his ten classes. The
> same with the categories and their complex natures - they are set up to
> examine and explain the world.
>
> My point is only that there is a lot of work being done now in the actual
> world, examining complex information dynamics - and Peirce's framework, to
> me, is perfect as an analytic tool for that purpose.
>
> I just wish we could expand the knowledge of this framework - and see how
> very pragmatic and enlightening it could be.
>
> Edwina
>
>
>
> On Mon 01/04/19 1:38 PM , Dan Everett danleveret...@gmail.com sent:
>
> This seems very exciting to me, Edwina. It fits exactly my own view of
> Peirce as coming up with ideas for empirical purposes. Even if someone were
> to think that you were stretching Peirce’s words (I don’t), it wouldn’t
> change the usefulness of what you are doing, I suspect.
>
> Thanks for sharing this stuff.
>
> Dan
>
> On Apr 1, 2019, at 1:35 PM, Edwina Taborsky <tabor...@primus.ca> wrote:
>
> List:
>
> I'm continuing with my interest in the pragmatics of Peircean semiosis;
> that is, the use of the Peircean analytic infrastructure to examine the
> dynamic operations within the organic chemical, the biological, the
> societal [economic systems, population behaviour] - and the cognitive
> [which includes AI].
>
> Basically, it's all about 'information processing' , which includes the
> self-organization of an organism's capacity and actions of knowledge
> development and maintenance, , adaptation of knowledge and behaviour,
> anticipation tactics, entropy problems and so on.
>
> Peirce provided us with an analytic infrastructure than enables us to
> examine the complexity within these actions. That is, his basic
> informational format is the semiosic triad of O-R-I, BUT, this triad is
> further broken down into more intricate 'nodal sites', and we end up with
> six: DO-IO-R-II-DI-FI. Such a framework enables more information
> transformation at each nodal site.
>
> In addition - Peirce provided the three categories of Firstness,
> Secondness and Thirdness - which are modes of organization of
> data/information. BUT again, he increased the complexity capacity of these
> three modes by introducing their so-called 'degenerate' forms: So- we have
> 1-1, 2-2 AND 2-1. Then, we have 3-3 AND 3-1 and 3-2. Note that Thirdness,
> the action of knowledge storage has THREE methods to carry out this action:
> iconic, indexical and symbolic. That's a powerful tool.
>
> Then, there are the ten basic classes of Signs - [2:254] - which explain
> the triads from the simple ''feeling' to the complex cognitive.  Put this
> all together and I maintain that Peirce has provided a powerful analytic
> framework for examining the dynamics - and it IS a dynamical operation - of
> information generation, adaptation, evolution and storage. These can, I
> suggest, be moved into the broader scientific world - and would be, I
> think, of great benefit.
>
> I'd like to refer to two articles as examples of how this Peircean
> framework could be put to use. I provide examples from  two reputable
> journals: Biosystems and Entropy. I note that neither deal
> with self-published works; the articles must go through a peer-review and
> revision process.
>
> The first article, from Biosystems, refers to the analogy between the
> biological realm and the work being done in AI.The focus is on
> 'Anticipation' - which is an ability generated by the mode of Thirdness.
> Understanding this mode and that there are THREE modes of Thirdness [which
> I have elsewhere referred to as strong and weak anticipation] would be, I
> suggest, of great benefit in the development of AI.
>
> The second article, from Entropy, also refers to the realm of Thirdness -
> to enable 'Interpretants/Understanding'. Again, this work sets up the act
> of 'anticipation' - and again, is focused on the development of AI.
>
> Essentially, my suggestion is that the complex framework of Peircean
> semiosis - with those Six nodal sites, those Six modal actions and ten
> classes - provides a powerful tool for the examination of complex processes
> in the real pragmatic world.
>
> Edwina
>
>
>
>
> 1]Anticipation: Beyond synthetic biology and cognitive robotics
> Author links open overlay panelSlawomir J.  Nasuto
> <https://www.sciencedirect.com/science/article/pii/S0303264716301551#!>
> Yoshikatsu  Hayashi
> <https://www.sciencedirect.com/science/article/pii/S0303264716301551#!>
> https://doi.org/10.1016/j.biosystems.2016.07.011
> open access
> Abstract
>
> The aim of this paper is to propose that current robotic
> <https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/robotics>
>  technologies cannot have intentional states any more than is feasible
> within the sensorimotor variant of embodied cognition. It argues that
> anticipation is an emerging concept that can provide a bridge between both
> the deepest philosophical theories about the nature of life and cognition
> and the empirical biological and cognitive sciences steeped in reductionist
> and Newtonian conceptions of  causality
> <https://www.sciencedirect.com/topics/pharmacology-toxicology-and-pharmaceutical-science/causality>
> .
>
>
> 2] The Understanding Capacity and Information Dynamics in the Human Brain
> Yan M. Yufik
> <https://www.mdpi.com/search?authors=Yan%20%20M.%20Yufik&orcid=>
> Virtual Structures Research, Inc., Potomac, MD 20854, USA
> Received: 23 December 2018 / Revised: 8 March 2019 / Accepted: 15 March
> 2019 / Published: 21 March 2019
> (This article belongs to the Special Issue Information Dynamics in Brain
> and Physiological Networks
> <https://www.mdpi.com/journal/entropy/special_issues/Physio_Networks>)
> Full-Text <https://www.mdpi.com/1099-4300/21/3/308/htm>   |    PDF
> <https://www.mdpi.com/1099-4300/21/3/308/pdf> [3517 KB, uploaded 29 March
> 2019]   |
> Figures
> ϕ1 (λ) to domain λk (adopted from [24]).
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g001.png";
> class="">zi and zk causes repetitive co-firing of neurons xn and xq and
> amplification of synaptic connections between them. As a result, the
> neuronal system receives information dI registered (absorbed) in the form
> of xn–xq synaptic link. (b ) Hebbian assembly emerges, as an aggregation
> of neurons that are tightly associated with each other due to their
> exposure to strongly correlated stimuli [ 34]. (c) Phase transition turns
> assembly into a quasi-stable packet Xα separated by boundary energy
> barrier from the surrounds. (d) Removing neurons from the packet requires
> expenditure of energy ΔE sufficient for overcoming the barrier.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g002.png";
> class="">Xα gives rise to the experience of object Oα projected into
> physical space outside the sensory surface (e.g., visual images are not
> experienced as irritations of the retina). Binding between object Oα and
> packet Xα is predicated on “bonding” in Xα (i.e., cohesion and relative
> stability of neuronal packets underlying the experience of external
> objects).
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g003.png";
> class="">Figure 1). Before the arrival of stimulus zi, the system was
> uncertain about the state of the environment; stimulus zi “primes” one of
> the packets, i.e., confines choices to a particular “domain” (packet), and
> thus predicts the likely stimuli composition (e.g., stimulus ZK ). Firing
> xq confirms (or disconfirms) the prediction. A series of confirmations
> amounts to recognizing the object (see Figure 3), while failed prediction
> motivate shifts to other packets.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g004.png";
> class="">Xα underlies the experience of object O α undergoing a series of
> state changes Qα1→Qα2→Qα3 . The object preserves its self-identity due to
> the preserved Oα –Xα binding (Qα1,  Qα2, Qα 3 are experienced as
> different states of object Oα ). (b) If population response vector is
> computed on the group of neurons in packet Xα , changes in Oα can be
> represented as rotation of the population vector. Different rotation
> trajectories define the behavior repertoire available to the object.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g005.png";
> class="">Ri connecting packet vectors in adjacent packets Xα and Xβ
> denotes ability to rotate packet vectors in a coordinated fashion, and to
> detect coordinated rotation.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g006.png";
> class="">
> <https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g007.png>
> ⊆A, C2 ⊆B can “interfacilitate” association between A and B [34]. ( b) It
> was suggested that overlapping activation results in the extraction of the
> overlap component C and formation of a triad, where the overlap component
> can coordinate alternatively with the other two members of the triad [ 30,
> 32].
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g008.png";
> class="">47]). “Call the forgotten thing Z, the first facts with which we
> felt it was related to a, b, and c, and the details finally operative in
> calling it up 1, m, and n. The activity in Z will at first be a mere
> tension; but as the activities in a, b, and c little by little irradiate
> into l, m, and n… their combined irradiations upon Z succeed in helping
> the tension there to overcome the resistance, and in rousing Z to full
> activity. Through hovering of the attention in the neighborhood of the
> desired object, the accumulation of associates becomes so great that the
> combined tensions of their neural processes break through the bar, and the
> nervous wave pours into the tract, which has so long been awaiting its
> advent” [47].
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g009.png";
> class="">A1—autism spectrum pathology, A2—Alzheimer’s spectrum
> pathology). T0 denotes optimal temperature.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g010.png";
> class="">ΔE1 → max. (b) The human CNS includes an extra regulatory loop
> (α loop), allowing manipulation of regulatory resources and engagement of
> sensory-motor resources in a manner decoupled from the overt sensory-motor
> activities. The extra loop is energy demanding but steeply increases
> regulatory efficiency by maximizing intakes and minimizing losses, ΔE2 →
> min. The understanding capacity derives from the operation of the loop.
>
> "
> href="https://www.mdpi.com/entropy/entropy-21-00308/article_deploy/html/images/entropy-21-00308-g011.png";
> class="">
> AbstractThis article proposes a theory of neuronal processes underlying
> cognition, focusing on the mechanisms of understanding in the human brain.
> Understanding is a product of mental modeling. The paper argues that mental
> modeling is a form of information production inside the neuronal system
> extending the reach of human cognition “beyond the information given”
> (Bruner, J.S.,  Beyond the Information Given, 1973). Mental modeling
> enables forms of learning and prediction (learning with understanding and
> prediction via explanation) that are unique to humans, allowing robust
> performance under unfamiliar conditions having no precedents in the past
> history. The proposed theory centers on the notions of self-organization
> and emergent properties of collective behavior in the neuronal substrate.
> The theory motivates new approaches in the design of intelligent artifacts
> (machine understanding) that are complementary to those underlying the
> technology of machine learning.  View Full-Text
> <https://www.mdpi.com/1099-4300/21/3/308/htm>
> Keywords: understanding <https://www.mdpi.com/search?q=understanding>;  mental
> models <https://www.mdpi.com/search?q=mental%20models>; information
> production <https://www.mdpi.com/search?q=information%20production>;  
> negentropy
> generation <https://www.mdpi.com/search?q=negentropy%20generation>
>
>
>
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