Re: [Fis] The State of the Art - Discussion of Information Science Education
Thank you, Bruno, John, Walter, Pedro, Gordana & FIS, I could not agree more with the said above. My only addendum to John’s argument to think about computation as "only one mode of information i.e. information AS cognitive process” is that computation should not be limited only to cognitive processes, but start earlier in biological development to and go all the way up to consciousness along the autopoietic tradition as shown in: http://www.slideshare.net/PriMate_PaTagOn/francisco-varela-a-calculus-for-selfreference-1707403 Bruno’s approach is also very interesting. We just finished our White Paper, the outcome of an almost one year joint effort within the INBIOSA project with contributions of Koichiro Matsuno, Stanly Salthe, Marcin Schroeder and other colleagues, and I wish to ask Pedro if it were appropriate to distribute this document within the FIS circle as a discussion base about information and computation in biological context. Best wishes, Plamen ___ ___ ___ Dr. Plamen L. Simeonov landline: +49.30.38.10.11.25 fax/ums: +49.30.48.49.88.26.4 mobile: +44.12.23.96.85.69 email: pla...@simeio.org URL: www.simeio.org On Sun, Dec 11, 2011 at 6:38 PM, Bruno Marchal wrote: > Hi John, Hi Fis-people > > > On 11 Dec 2011, at 13:49, john.holg...@ozemail.com.au wrote: > > Thanks Walter, > > A useful snapshot of PC (Philosophy of Computing). It reminds me that the > origin of the word 'computing' is com-putare = to consider together, > suppose together, imagine together. This is surely what Steve Jobs was all > about. To reduce computation to algorithmic calculation or even Turing > machines is as restrictive as limiting information to data and documents, > messages and codes. After thirty years of phronesis wrestling with data > documents and computers it would be nice to know what computation and > information mean. > > > It might be restrictive at the epistemological level, but not necessarily > at the ontological level. All mathematical notions, like infinities, sets, > provability, definability, etc. can be diagonalized again. They cannot have > a universal representation. But computability and computations are immune > to diagonalization. This makes it the concept the most explanatively closed > we have ever found. I think. This gives a conceptual deep argument in favor > of Church thesis, and it leads also to the notion of universal machines. > > Those machines can not only compute the same class of all (partial or > total) computable functions, but can all simulate each other, computing > those functions in all possible different ways. > Actually, an interesting and vast class of universal machines (those who > knows, in some technical sense, that they are universal) can defeat any > theory concerning their own behavior (they can practice diagonalization), > making their epistemologies beyond any normative or effectively complete > theory. It makes computationalism (the doctrine that there exists a level > where we are Turing emulable) a vaccine against reductionist conception of > machine (and man). > > I am Bruno Marchal, mathematician, and I met Pedro and Plamen in Paris > some month ago. Although I am agnostic on the truth of the computationalist > hypothesis in the cognitive science, I am interested to study the mind body > problem in that frame. With the computationalist hypothesis, computer > science and mathematical logic becomes handy tools for formulating deep > questions. > > In fact I have a deductive argument that computationalism and weak > materialism (there exist an ontologically primary physical universe) are > incompatible. I have shown that computationalism reduces (in my french PhD > thesis in computer science) the mind body problem into a body appearance > (to universal numbers) problem in number theory. > > Physics would not be the fundamental science, and we might have to > backtrack to Plato, or even Pythagorus' conception of reality. Physical > reality becomes somehow the border of a universal mind (the possible > universal machine dreams, or the effective set of all computations seen > from inside. The "seen from inside" can be defined from the modal logic of > self-reference, which exploits that immunity for diagonalization, and the > fact that machines can be "aware" of that fact. > > The following two papers sum up the main results and questions needed to > solve to proceed: > > http://iridia.ulb.ac.be/~marchal/publications/SANE2004MARCHALAbstract.html > > http://iridia.ulb.ac.be/~marchal/publications/CiE2007/SIENA.pdf > > Unfortunately the longer version of those works are in french (they can be > found from my URL below). > > This might perhaps put some light on the difficult question of what is > information. Like infinite, and like almost all in-# notions, that notion > might not have a definitive definition, especially *information* which > walked from syntactic definitions (Shannon) to semantical one (knowledge). > > > > Computation is only
Re: [Fis] The State of the Art - Discussion of Information Science Education
2011/12/9 : > Dear all, > I teach every year (this fall fourth time) a general education > course Information Science for freshmen and sophomores which > has as its main objective to present not an existing > discipline, but a potential unified approach to study complex > issues related to globalization. Globalization is a leitmotif > of the curriculum at our university. I am trying to show that > the concept of information, although not very clearly defined > yet, can be useful in dealing with several fundamental > problems for the future of humanity. I am giving short and > very general expositions of topics such as, language and other > forms of communication, telecommunication, cryptography, > genetics, life and organism, computation. Then we are trying > to identify what makes the mechanisms involved > similar, and the expected answer is "information". I am > referring to the five great metaphors in the history of > Western Thought, which were used to model reality: Human > organism (as microcosm to explain functioning of macrocosm in > medieval interpretations of neoplatonism), mechanical clock, > steam machine, telecommunication, computer. In each case, I am > showing the presence of the intuitive concept of information. > Finally, I am presenting analysis of global warming, > pandemics, and other threats to humanity from the unified > perspective of information. > The biggest problem for me is to find materials for students > which are not exceedingly detailed and difficult, but also not > trivial. Do you have any suggestions? > Regards, > Marcin > > ___ > fis mailing list > fis@listas.unizar.es > https://webmail.unizar.es/cgi-bin/mailman/listinfo/fis Dear Colleagues, On the basis of papers [1-7] I designed course “Physical informatics”, focused primarily on graduate students and masters. The basic course content: 1. General provisions. Background information about the information and informatics. 2. The subject of physical informatics. 3. Classes of physical systems and their characteristics. 4. Information characteristics of physical systems and methods for their determination. •Information entropy: the characteristic obserables and states of quantum systems, a measure of complexity of systems. •Information divergence: a heterogeneity measure. •Joint information entropy: the characteristic of unitary transformations. •The mutual information: the characteristic of interaction of the linked (entanglement) systems. •The Differential information capacity - characteristic of volume of information per unit mass. 5. The laws of informatics •The law of simplicity of complex systems. •The law of uncertainty (information) conservation. •The law of finiteness of complex systems characteristics. •The law of necessary variety by W. Ashby. •The theorem of K. Gödel. •Other laws of informatics. 6. The physical laws as consequence of information laws (laws of informatics). 7. Methodology assessment and evaluation of information characteristics of fundamental and elementary particles, atoms, molecules, gases, liquids, solids, planets, stars, galaxies and the universe as a whole. 8. Informational constraints on the formation, development and interconversion of physical systems. 9. Information system for calculating the characteristics of physical systems. 10. Features of researches by information methods of chemical and biological systems. 11. The forms of the organization of the researches. 12. The main objectives for further research. 13. Conclusion 14. The application. A.1. The primary information needed from physics, chemistry, and biology. A.2. The necessary information from information theory. A.3.Test Questions and exercise. Literature. 1. Gurevich I.M. The laws of informatics - the basis of research and design of complex communications and control systems. Manual. TSOONTI "Ecos". M. 1989. 60 p. 2. Gurevich I.M. "The laws of informatics - the basis of the structure and knowledge of complex systems." - M. "Antiqua", 2003. 3. Gurevich I.M. "The laws of informatics - the basis of the structure and knowledge of complex systems." Second edition refined and updated. M. "Torus Press." 2007. 400 p. 4. Gurevich I.M. Assessment of the main characteristics of the information universe. Information Technology. № 12. Application. 2008. 32. 5. Gurevich I.M. Information characteristics of physical systems. "The 11th FORMAT". Moscow. "Cypress". Sevastopol. 2009. 170 p. 6. Gurevich I.M. Information characteristics of physical systems. Second edition refined and updated. "Cypress". Sevastopol. 2010. 260 p. 7. Gurevich I.M. Information as a universal heterogeneity. Information Technology. № 4. M. 2010. Pp. 66-74. 8. Gurevich I.M. Basic information characteristics of physical, chemical and biological systems. Modern Trends in Theoretical and Applied Biophysics, Physics and Chemistry. BPPC - 2010. Vol. 1. Common Questions of Physics and Chemistry: materials of VI International s
Re: [Fis] The State of the Art - Discussion of Information Science Education
Hi All,
the talk here going about a possible curriculum, I have assembled one. This
is of course only an outline but should give a realistic idea about the
half-steps needed to grasp what we understand under "information". I'd look
forward working on this project. Asking for your kind tolerance, I present
the:
Curriculum (15 hrs) Additions
Requirements: able to program and manage data sets
Aim: understand ordering, reordering, spatial structures, consequences
(implications)
Part I.: Tabulating
1.
We use a collection of additions: We use {1+1..16+16}, a≤b; Why 136
2.
Sorting and sequencing: (The meaning of the term ‘sequence’ in the
sentence ‘The DNA is a sequence’); assignment of i (1≤i≤136); creating
linear distances; partitioning 136; homogenizing sub-intervals; kinds of
cuts
3.
Resorting from SQab into SQba and back: Terms place-space (a
seq.no1..136 is a place in a 1-dim space); place changes; moving
together
(example in classroom, games); properties of chains (1,1 stays, 1,2 stays,
1,3 travels: 18 steps); Table (=data set) T (T_άβ_γδ_i_j_placeάβ_placeγδ,
where άβ from, γδ to, i-th chain, j-th step, this example T_ab_ba_3_1 3 4)
4.
Creating a plane by rectangular axes: example SQab, SQba as axes. Follow
movement. Discuss terms string, loop, convoy, melody, tact, beat
5.
Additional aspects of a+b=c: central: u=b-a; two shadows: b-2a, a-2b;
create 2b-3a, 2a-3b; (mention costs of commutativity), just for fun
s=17-{a+b|c}
6.
Sorting on aspects a thru w: presently in this sequence, later play with
changing sequence of first-level arguments; generate 72 SQs, assemble Table
1 (81 cols, 136 rows)
7.
Identical sequences and clans: of a clan, the first we encounter is the
chief, the others use his name as alias but give weight; Vector V:
if(SQάβ=SQγδ, .t., .f.); if(V[άβ,γδ], member of a clan, reorder); fill up
Table T
8.
Overview of resorts: Table S, S_άβ_γδ_i_J, where άβ from, γδ to, i-th
chain, J no of steps, this example T_ab_ba_3_1 3 18); carry_a (=Σa); goods
in transit
9.
Standard resorts: Properties; (6+11=17 as the quintessential magical
incantation); names; weights (clans); three-somes
10.
Building space: Rectangular axes; planes;
11.
The concept of a point in space: two exact subspaces; one rough estimate
of a space; (the loss of an accounting property); units of three-somes;
Representation as a triangle, center of triangle: mass point in space;
rotating the axes; volume included, spherical or rectangular
representation; goods transited thru this segment
12.
Connection to other points: isolator and conductor (if(.exist.Δγδ
(triangle) in chains connecting each of 3 points of Δάβ), conductor,
isolator); not each of 3 points connected: too near .or. too far;
telekratic effects
Part II.: Sequencing
1.
Permutating first-level arguments a…w: cause and effect within an
interdependence; implicated orders; ties
2.
The idea of time: basic to sequencing, predecessor, successor;
demonstrating effects of sequence changes; linguistics as mediator (Table
V, number of .t., sequence of comparisons)
Part III. Giving names
1.
Mass, space, density, electric-magnetic, gravity, temperature, chemical
valence: always check with established authorities before assigning a name
- end curriculum --
2011/12/11 Bruno Marchal
> Hi John, Hi Fis-people
>
>
> On 11 Dec 2011, at 13:49, john.holg...@ozemail.com.au wrote:
>
> Thanks Walter,
>
> A useful snapshot of PC (Philosophy of Computing). It reminds me that the
> origin of the word 'computing' is com-putare = to consider together,
> suppose together, imagine together. This is surely what Steve Jobs was all
> about. To reduce computation to algorithmic calculation or even Turing
> machines is as restrictive as limiting information to data and documents,
> messages and codes. After thirty years of phronesis wrestling with data
> documents and computers it would be nice to know what computation and
> information mean.
>
>
> It might be restrictive at the epistemological level, but not necessarily
> at the ontological level. All mathematical notions, like infinities, sets,
> provability, definability, etc. can be diagonalized again. They cannot have
> a universal representation. But computability and computations are immune
> to diagonalization. This makes it the concept the most explanatively closed
> we have ever found. I think. This gives a conceptual deep argument in favor
> of Church thesis, and it leads also to the notion of universal machines.
>
> Those machines can not only compute the same class of all (partial or
> total) computable functions, but can all simulate each other, computing
> those functions in all possible different ways.
> Actually, an interesting and vast class of universal machines (those who
> knows, in some technical sense, that
