Alan Mathison
Turing
A. M. Turing
Regresar a Personajes Fundamentales de la Informática Regresar a www.fgalindosoria.org Alan Mathison Turing A. M.
Turing
The
Rutherford Journal, The New
Zealand Journal for the History and Philosophy of Science and Technology Volume 4,
2011-2012 This
Special Issue for the 2012 Alan Turing Centenary Year is a web-book: Alan Turing, Father of the Modern Computer http://www.rutherfordjournal.org/current3.html http://www.rutherfordjournal.org/article040101.html Alan Turing Artificial Intelligence 'Gooware', gooware computer,
Unorganized machine, ACE Computer (Automatic Computing
Engine), Chemical computer, Belousov–Zhabotinsky reaction / Reacción
de Beloúsov-Zhabotinski, Alan Turing Wikipedia, (20160612) Alan Mathison Turing OBE FRS (/ˈtjʊərɪŋ/; 23
June 1912 – 7 June 1954) was a pioneering English computer scientist, mathematician,
logician, cryptanalyst
and theoretical biologist. He
was highly influential in the development of theoretical computer science,
providing a formalisation of the concepts of algorithm
and computation
with the Turing machine, which can be considered a model of
a general purpose computer. Turing is widely considered to be the father of
theoretical computer science and artificial intelligence. During the Second
World War, Turing worked for the Government Code and Cypher
School (GC&CS) at Bletchley
Park, Britain's codebreaking centre. For a time he led Hut 8, the
section responsible for German naval cryptanalysis. He devised a number of
techniques for breaking German ciphers, including improvements to the pre-war Polish bombe method and an electromechanical
machine that could find settings for the Enigma
machine. Turing played a pivotal role in cracking intercepted coded
messages that enabled the Allies to defeat the Nazis in many crucial
engagements, including the Battle of the Atlantic; it has been
estimated that this work shortened the war in Europe by as many as four years.[6] After the war,
he worked at the National Physical Laboratory,
where he designed the ACE, among the first designs for a
stored-program computer. In 1948 Turing joined Max Newman's
Computing Machine Laboratory at the Victoria University of Manchester,
where he helped develop the Manchester computers[7]
and became interested in mathematical biology. He wrote a paper on
the chemical basis of morphogenesis, http://en.wikipedia.org/wiki/Alan_Turing ************************************************** ‘On
Computable Numbers, With an Application to The Entscheidungsproblem’ A. M.
Turing 1936 Computing
Machinery & Intelligence’, aparecido en la revista Mind (1950), Beyond
Turing's Machines ************************************************** Alan
Turing's most profound achievement is arguably the principle of a universal
machine that makes logic rather than arithmetic the computer's driving force,
writes the University of Oxford's Andrew Hodges. Turing also defined the
concept of computability, and suggested that mathematical steps that do not
follow rules, and are thus not computable, could be identified with mental
intuition. His 1950 treatise presented a basic argument that if the brain's
action is computable, then it can be deployed on a computer or universal
machine. Turing later suggested that modeling of the human brain might be
impossible because of the nature of quantum mechanics, and his view of what
is computable has not changed despite the advent of quantum computing. Many
thought-experiment models investigate the implications of going beyond the
constraints of the computable, and some require that machine elements operate
with unlimited speed or permit unrestricted accuracy of measurement. Others
more deeply explore the physical world's nature, with a focus of how mental
operations relate to the physical brain and the need to rethink quantum
mechanics because uncomputable physics is basic to physical law. Hodges says
this way of thinking is part of Turing's legacy even though it superficially
runs counter to his vision. http://technews.acm.org/archives.cfm?fo=2012-04-apr/apr-20-2012.html#578693 Turing on
Computation, Memory and Behavior Eli
Dresner The
Rutherford Journal, Volume 3, 2010 The New
Zealand Journal for the History and Philosophy of Science and Technology http://www.rutherfordjournal.org/article030104.html ************************************************** ************************************************** Bekenstein
bound “In physics,
the Bekenstein bound is a conjectured limit on the entropy S or information
that can be contained within a region of space containing a known energy. It
implies that information must be material, requiring finite size and energy.
In computer science, this implies that there is a maximum information
processing rate and that Turing
machines, with their (by definition) infinite memory tape, are physically
impossible if they are to have a finite size and bounded energy. The bound
was originally found by Jacob
Bekenstein in the form where R
is loosely defined as the radius of the region, and E is the energy of
the contained matter as measured when the matter is moved to an infinite
distance, i.e., accounting for binding force potential energies. Note that
while gravity plays a significant role in its enforcement, the bound is
independent of Newton's Constant G.”
(Wikipedia May 25, 2009) http://en.wikipedia.org/wiki/Bekenstein_bound http://www.fgalindosoria.org/informatica/informaticos/fundamentales/Jacob_David_Bekenstein/ ************************************************** ************************************************** BLOG La Singularidad Desnuda Un universo impredecible de pensamientos y cavilaciones sobre ciencia, tecnología y otros conundros http://singularidad.wordpress.com/ Incluye temas como Turing en una cáscara de nuez: No computabilidad http://singularidad.wordpress.com/2007/04/20/turing-en-una-cascara-de-nuez-no-computabilidad/ Gödel en una cáscara de nuez: Primer Teorema de Incompletitud Gödel en una cáscara de nuez: Segundo Teorema de Incompletitud, y Teorema de Completitud Gödel en una cáscara de nuez: La diagonalización de Cantor Turing en una cáscara de nuez: Teorema de Rice (o por qué ningún
antivirus será fiable al 100%) Turing en una cáscara de nuez: castores afanosos y la paradoja
de Berry Turing en una cáscara de nuez: Complejidad de Kolmogorov ************************************************** ************************************************** Morphogenetic field Morphogenetic
fields are defined by
Sheldrake as the subset of morphic fields which influence, and are influenced
by living things. “The term
[morphic fields] is more general in its meaning than morphogenetic fields,
and includes other kinds of organizing fields in addition to those of
morphogenesis; the organizing fields of animal and human behaviour, of social
and cultural systems, and of mental activity can all be regarded as morphic
fields which contain an inherent memory.” — Sheldrake, The
Presence of the Past (Chapter 6, page 112) (Wikipedia October 20, 2008) http://en.wikipedia.org/wiki/Morphic_field#Morphogenetic_field Campo morfogenético “En el marco teórico de la evolución biológica, el campo morfogenético, hipótesis de los campos morfogenéticos, o campos mórficos, sería el nombre dado por Rupert Sheldrake a un campo hipotético que explicaría la evolución simultánea de la misma función adaptativa en poblaciones biológicas no contiguas Morfo viene de la palabra griega morphe, que significa
forma. Los campos morfogenéticos son campos de forma; campos, patrones o
estructuras de orden. Estos campos organizan no solo los campos de organismos
vivos sino también de cristales y moléculas. Cada tipo de molécula, cada
proteína por ejemplo, tiene su propio campo mórfico -un campo de hemoglobina,
un campo de insulina, etc. De igual manera cada tipo de cristal, cada tipo de
organismo, cada tipo de instinto o patrón de comportamiento tiene su campo
mórfico. Estos campos son los que ordenan la naturaleza. Hay muchos tipos de
campos porque hay muchos tipos de cosas y patrones en la naturaleza..." Rupert Sheldrakebold (Wikipedia, 20 de Octubre del 2008) http://es.wikipedia.org/wiki/Campo_morfogen%C3%A9tico Teoría Sintérgica Jacobo Grinberg Zylberbaum “Nosotros interactuamos con una matriz informacional o campo informacional que todo lo abarca y envuelve y que contiene en cada una de sus porciones toda la información. Es una matriz de tipo holográfico. En ese nivel de cualidad de la experiencia no hay objetos separados unos de otros, sino que se trata de un extraordinario campo informacional de enorme complejidad. Nuestro cerebro interactúa con ese campo informacional que algunos llaman campo cuántico y otros como David Böhm, el orden implicado. Los físicos actuales hablan de un campo espacial y la Teoría Sintergica de Grinberg la denomina campo sintérgico.” (Ligado, 20 de Octubre del 2008) http://www.neuralterapeuticum.org/microtubulos/info01.htm Rupert
Sheldrake “Sheldrake was
born in Newark-on-Trent, Nottinghamshire and grew up there. He studied
biochemistry at Clare College, Cambridge, graduating with a Double First-Class Honours degree. He was a Frank Knox fellow at Harvard,
studying philosophy
and history.
He returned to Cambridge where he gained a PhD in biochemistry and was a
Fellow at Clare College. He was a Research Fellow of the Royal
Society and later went to Hyderabad, India where he was
Principal Plant Physiologist at the International Crops Research Institute
for the Semi-Arid Tropics (ICRISAT). For
a year and a half he lived in the ashram of Bede
Griffiths.” (Wikipedia October 20, 2008) http://en.wikipedia.org/wiki/Rupert_Sheldrake Rupert
Sheldrake “Los campos morfogenéticos o campos mórficos llevan información, no energía, y son utilizables a través del espacio y del tiempo sin perdida alguna de intensidad después de haber sido creados. Son campos no físicos que ejercen influencia sobre sistemas que presentan algún tipo de organización inherente.” (Wikipedia, 20 de Octubre del 2008) http://es.wikipedia.org/wiki/Rupert_Sheldrake Morfogénesis y emergencia de patrones en sistemas biológicos: del rompimiento de simetría a la autoorganización y la excitabilidad Dr. Faustino Sánchez “Este capítulo expone de manera conceptual algunos mecanismos subyacentes a la emergencia de patrones en sistemas biológicos, así mismo presenta su formulación matemática y algunos ejemplos.” http://www.iieh.com/complejidad/articulos_complejidad06.php Dinámica inducida a través de resonancia espacial de patrones estacionarios de Turing David Gómez Míguez Memoria realizada en el Departamento de Física de Materia Condensada de la Universidad de Santiago de Compostela para optar al grado de Licenciado en Física. Mayo, 2002 “Es sabido que
multitud de sistemas descritos por ecuaciones no lineales (químicos,
biológicos, ópticos, astrofísicos...), mantenidos lejos de su equilibrio
ter-modinámico, pueden producir patrones estacionarios en medios
espacialmente ex-tendidos, debido a una rotura de simetría, lo cual implica
una diferencia en alguna de las propiedades del sistema si comparamos
diferentes puntos espaciales del mismo. Alan Turing [Turing, 1952] anticipó la idea de que bajo ciertas condiciones, dos procesos antagónicos, uno activador y otro inhibidor de la producción de uno de los reactivos de la reacción, pueden generar una rotura de simetría.” Turing A.
M., [1952] “The Chemical Basis of Morphogenesis,” Philos. Trans. R http://people.brandeis.edu/~miguez/descargas/tesina_David_G_Miguez.pdf ************************************************** ************************************************** ¿Pueden Pensar las Máquinas? A.M. Turing, Computing Machinery
and Intelligence A.R. Anderson et alia (eds.), Mentes y máquinas (México: UNAM, 1974). http://claudiogutierrez.com/bid-fod-uned/Turing.html Por qué la gente piensa que los computadores no pueden Marvin Minsky,
"Why People Think Computers Can't", AI Magazine,1982. http://www.claudiogutierrez.com/bid-fod-uned/MarvinMinsky.html ************************************************** Turing test “The Turing test is a proposal for a test of a machine's ability to demonstrate intelligence. Described by Alan Turing in the 1950 paper "Computing Machinery and Intelligence," it proceeds as follows: a human judge engages in a natural language conversation with one human and one machine, each of which try to appear human; if the judge cannot reliably tell which is which, then the machine is said to pass the test.” (Wikipedia October 23, 2008) http://en.wikipedia.org/wiki/Turing_test Prueba de Turing “La prueba consiste en un desafío. Se supone un juez situado en una habitación, y una máquina y un ser humano en otras. El juez debe descubrir cuál es el ser humano y cuál es la máquina, estándoles a los dos permitidos mentir al contestar por escrito las preguntas que el juez les hiciera. La tesis de Turing es que si ambos jugadores eran suficientemente hábiles, el juez no podría distinguir quién era el ser humano y quién la máquina.” (Wikipedia, 23 de Octubre del 2008) http://es.wikipedia.org/wiki/Prueba_de_Turing Premio Loebner en Inteligencia Artificial, un concurso de carácter anual que se celebra desde 1990 y que somete a varios ordenadores a la Prueba de Turing. Home Page
of The Loebner Prize in Artificial Intelligence "The
First Turing Test" “The
Loebner Prize for artificial intelligence ( AI
) is the first formal instantiation of a Turing Test.” http://www.loebner.net/Prizef/loebner-prize.html 18th Annual Loebner Prize for Artificial
Intelligence http://loebner.net/Prizef/2008_Contest/loebner-prize-2008.html A New
Interpretation of the Turing Test Diane
Proudfoot The
Rutherford Journal, Volume 1, 2005-2006 The New
Zealand Journal for the History and Philosophy of Science and Technology The Turing
Test and the Orthodox Interpretation In
‘Computing Machinery and Intelligence’ (1950) Turing described an ‘imitation
game’ played by three people, an interrogator and two interviewees, one male
(A) and one female (B). The interrogator communicates with A and B from a
separate room (by means of printed text and nowadays probably using a
keyboard and screen); apart from this the three players have no contact with
each other. The interrogator’s task is to find out, by asking questions,
which of A and B is the man. A’s aim is that the interrogator decide wrongly.
(Turing said, ‘The object of the game for the third player (B) is to help the
interrogator. The best strategy for her is probably to give truthful
answers.’ (1950, p. 434).) In a
second version of the game, a computer takes the part of A
and a male or female the part of B.1 Now the interrogator’s task is to discover which of A and B is the
computer; to do so he or she is permitted to ask any question, on any topic.
The computer is allowed to do everything possible so that the interrogator
makes the wrong identification. Turing said that the question ‘Can machines
think?’ is ‘too meaningless to deserve discussion’ and proposed replacing it
by the question ‘Are there imaginable digital computers which would do well
in the [computer-imitates-human] game?’ (ibid., p. 442). The upshot of his
famous proposal is: if some computer does well in the imitation game, the
answer to (an appropriate substitute for) the question ‘Can machines think?’
is ‘yes’. Hence Turing offers a test of intelligence in machines. http://www.rutherfordjournal.org/article010113.html UK university
holds artificial intelligence test By RAPHAEL G.
SATTER, READING, England Associated
Press October 13, 2008 http://ap.google.com/article/ALeqM5g9jhLygsbJ5Am-GtNIP7jVt7EdwgD93PIS207 Breves explicaciones acerca de tópicos básicos de la inteligencia artificial http://members.fortunecity.es/rednovohcop/mccdex.html www.fgalindosoria.org/areas/ai/ ************************************************** ************************************************** Constante de Chaitin “La constante de Chaitin es un número entre 0 y 1. Es la
probabilidad que un programa elegido al azar detenga correctamente a una
máquina de Turing determinada. Sea P el conjunto de todos los programas que se
detienen, y |p| el tamaño en bits de un programa p, Ω está
definida de la siguiente manera: Esta constante no es computable. Es posible conocer los
primeros decimales, pero a partir de cierto decimal (que depende de la
codificación elegida) no es posible saber más decimales.” http://es.wikipedia.org/wiki/Constante_de_Chaitin Chaitin's
constant “In the
computer science subfield of algorithmic information theory a Chaitin
constant or halting probability is a real number that informally represents
the probability that a randomly-chosen program will halt. These numbers are
formed from a construction due to Gregory Chaitin. Although there
are infinitely many halting probabilities, it is common to use the letter
Ω to refer to them as if there were only one. Because Ω depends on
the program encoding used, it is sometimes called Chaitin's construction
instead of Chaitin's constant when not referring to any specific encoding. Each halting
probability is a normal and transcendental real number which is definable but
not computable, which means that there is no halting algorithm that
enumerates its digits.” http://en.wikipedia.org/wiki/Chaitin%27s_constant Good–Turing
frequency estimation “Good–Turing
frequency estimation is
a statistical technique for predicting the probability of occurrence of
objects belonging to an unknown number of species, given past observations of
such objects and their species. (In drawing balls from an urn, the 'objects'
would be balls and the 'species' would be the distinct colors of the balls
(finite but unknown in number). After drawing Rred
red balls, Rblack black balls
and Rgreen green balls, we would
ask what is the probability of drawing a red ball, a black ball, a green ball
or one of a previously unseen color.)” http://en.wikipedia.org/wiki/Good-Turing_frequency_estimation UCSD scientists
explain and improve upon 'enigmatic' probability formula Findings could
have implications for speech recognition, machine learning, information
retrieval Contact: Doug
Ramsey, San Diego, Oct. 16, 200 “Scientists at
the University of California, San Diego (UCSD) have developed new insight
into a formula that helped British cryptanalysts crack the German Enigma code
in World War II. Writing in the Oct. 17 edition of the journal Science, UCSD
Jacobs School of Engineering professor Alon Orlitsky and graduate students
Narayana P. Santhanam and Junan Zhang shed light on a lingering mathematical
mystery and propose a new solution that could help improve automatic speech
recognition, natural language processing, and other machine learning
software. In the article,
Orlitsky and his colleagues unlock some of the secrets of the
"Good-Turing estimator," a formula for estimating the probability
of elements based on observed data.” http://www.eurekalert.org/pub_releases/2003-10/uoc--use101603.php ************************************************** ************************************************** Unorganized machine From Wikipedia, the free encyclopedia (20121214) “An unorganized machine is a concept
mentioned in a far-sighted 1948 report in which Alan Turing suggested
that the infant human cortex was what he called an "unorganized
machine".[1][2] Turing
defined the class of unorganized machines as largely random in their initial
construction, but capable of being trained to perform particular tasks.
Turing's unorganized machines were in fact very early examples of
randomly-connected, binary neural networks, and
Turing claimed that these were the simplest possible model of the nervous system. Turing had been interested in the possibility of
simulating neural systems for at least the previous two years. In
correspondence with William
Ross Ashby in 1946 he writes: "I am more interested in the possibility of
producing models of the action of the brain than in the applications to
practical computing...although the brain may in fact operate by changing its
neuron circuits by the growth of axons and dendrites, we could nevertheless
make a model, within the ACE, in which
this possibility was allowed for, but in which the actual construction of the
ACE did not
alter, but only the remembered data"” http://en.wikipedia.org/wiki/Unorganized_machine ************************************************** ************************************************** ACE Computer Automatic Computing Engine From Wikipedia, the free encyclopedia (20121214)
Pilot ACE “The Automatic Computing Engine (ACE) was an early electronic stored-program computer
design produced by Alan Turing at the invitation of John R. Womersley,
superintendent of the Mathematics Division of the National Physical Laboratory (NPL). The use of the word Engine was in homage to Charles
Babbage and his Difference Engine and Analytical Engine. Turing's technical design Proposed
Electronic Calculator was the product of his theoretical work in 1936
"On Computable Numbers"[1]
and his wartime experience at Bletchley
Park where the Colossus computers had been successful in
breaking German military codes. In his 1936 paper, Turing described his idea
as a "universal computing machine", but it is now known as the Universal Turing machine.” http://en.wikipedia.org/wiki/Automatic_Computing_Engine ************************************************** ************************************************** Discovery of a Prototype Hollerith Machine in Paris David Anderson, Janet Delve and Hans Pufal The Rutherford Journal, Volume 1, 2005-2006 The New Zealand Journal for the History and
Philosophy of Science and Technology Preamble Probably the oldest surviving example of the
Hollerith Tabulating Machine is to be found in Paris as part of the
collection of the Conservatoire des Arts et Métiers (CNAM).
Unfortunately Hollerith’s device is not on general display but is in the CNAM reserves stored on a pallet at a height of almost 2 metres above floor level making examination on a first
visit quite difficult. http://www.rutherfordjournal.org/article010108.html ************************************************** ************************************************** Researchers Developing Alan Turing Artificial
Intelligence 'Gooware' V3.co.uk (12/07/12) ”University of the West of England researchers have
made progress in building a "gooware" computer,
based on Alan Turing’s idea of "unorganized machines." Turing
argued the simplest form of an unorganized machine would be a randomly
connected network of NAND logic gates, known as
A-type machines. The West of England researchers are focusing on an unusual
group of chemical reactions called Belousov-Zhabotinsky
(BZ) reactions. These reactions do not reach a
stable equilibrium point, and subtle stimuli can produce patterns in a
normally calm mixture. The waves of chemical changes in the BZ reaction are used as the basis of transferring
information. A processor made from a BZ reaction
could potentially move information in any direction and handle more data than
a traditional computer. The researchers have also shown that they can use
their BZ NAND gate as the
basis of an A-type unorganized machine. "It was then shown how a number
of well-known benchmark logic gates can be designed from A-type unorganized
machines using an approach inspired by a comment from Turing on cultural
search," according to the researchers.” ACM TechNews, Friday,
December 14, 2012 http://technews.acm.org/#623866 Researchers developing Alan Turing artificial
intelligence 'gooware' 07 Dec 2012 ************************************************** ************************************************** Algoritmos Evolutivos, Curso 2009 Centro de Cálculo, Instituto de Computación, Facultad de Ingeniería, Universidad de la República, Uruguay. “Los programas “autoreplicables” y “evolutivos” fueron sugeridos desde los inicios de la era de la computación. Alan Turing Neumann János Reseña histórica • Las primeras ideas se formulan entre 1948 y 1960. • Alan Turing investigó las relaciones sobre evolución natural y aprendizaje. Propuso el desarrollo de programas automodificables, capaces de jugar ajedrez y simular otras actividades inteligentes sencillas, utilizando técnicas evolutivas. • Neumann János trabajó sobre autómatas celulares evolutivos. Propuso mecanismos evolutivos para implementar autómatas con poder computacional equivalente a una máquina de Turing. Conjeturó sobre poblaciones de autómatas trabajando cooperativamente y comunicándose entre sí. (“Teoría de autómatas autorreplicables”, texto inconcluso, 1966).” http://www.fing.edu.uy/inco/cursos/geneticos/ae/2009/Clases/clase2-2009.3x1.pdf http://www.fgalindosoria.org/eac/evolucion/links/History.htm ************************************************** ************************************************** Bletchley
Park's Sturgeon, the Fish that Laid No Eggs Frode
Weierud The
Rutherford Journal, Volume 1, 2005-2006 The New Zealand
Journal for the History and Philosophy of Science and Technology Introduction The
German armed forces employed three different types of teleprinter cipher
machines during the Second World War, the Lorenz machines SZ40 and SZ42 also
called Tunny by Bletchley Park (BP), the Siemens & Halske
Schlüsselfernschreibmaschine (SFM) T52, and the one-time-tape machine T43,
also manufactured by Siemens.1 The Lorenz machines, which existed in three different models, SZ40,
SZ42a, and SZ42b, are well known as the machines that were broken at BP with
the aid of Colossus. The Siemens T52 existed in four functionally distinct
models, T52a/b, T52c and T52ca - which was a modified version of the T52c machine,
T52d, and T52e, all going under the BP code name of Sturgeon, while the
Siemens T43 probably was the unbreakable machine that BP called Thrasher. The
T43 machine came into use relatively late in the war and appears to have been
used only on a few selected circuits. This
paper will explain in detail the events that led to BP breaking the Sturgeon
machines. In 1964, the Swedish Under-Secretary of State Erik Boheman first
revealed that Sweden had broken the German Geheimschreiber (T52) during the
Second World War. In 1967, David Kahn gave further details about this
achievement. However, it was only in 1984, when Hinsley et al. published part
one of the third volume of "British Intelligence in the Second World
War," that it was officially acknowledged that BP also had experienced
some success against the Siemens T52. Previously, many authors had confused
the T52 with the Lorenz SZ40/42 machines and had erroneously linked the
Siemens T52 to Colossus. Since 1982, Donald Davies has published detailed
information about the electrical and mechanical construction of the machines.
And Wolfgang Mache has through his contacts and interviews with former
Geheimschreiber operators and technicians presented the evolutionary history
of the Siemens T52 machines. Apart from Sir Harry Hinsley's and Professor
Tutte's references to BP's attack against the T52 there had not been any
detailed account of this part of BP's history before an earlier, shorter
version of this paper was published in 2000. http://www.rutherfordjournal.org/article010106.html The
Turing Bombe Frank
Carter The
Rutherford Journal, Volume 3, 2010 The New
Zealand Journal for the History and Philosophy of Science and Technology http://www.rutherfordjournal.org/article030108.html Colossus:
Breaking the German ‘Tunny’ Code at Bletchley Park. An Illustrated History B. Jack
Copeland The
Rutherford Journal, Volume 3, 2010 The New
Zealand Journal for the History and Philosophy of Science and Technology http://www.rutherfordjournal.org/article030109.html ************************************************** ************************************************** The
ACM A.M. Turing Award is ACM's most prestigious technical award. It
recognizes contributions of lasting and major technical importance, and
honors Turing Award From Wikipedia, the free encyclopedia
The ACM A.M.
Turing Award is an annual prize given by the Association for Computing
Machinery (ACM) to "an individual selected for contributions of a
technical nature made to the computing community". It is stipulated that
"The contributions should be of lasting and major technical importance
to the computer field".[1] The Turing
Award is recognized as the "highest distinction in Computer
science"[2]
and "Nobel Prize of computing".[3] http://en.wikipedia.org/wiki/Turing_Award ************************************************** ************************************************** The Mathematic Model of Consciousness AMS '08:
Proceedings of the 2008 Second Asia International Conference on Modelling
& Simulation (AMS) - Volume 00 , Volume 00, May 2008 Publisher: IEEE
Computer Society Abstract “The
thought referring homomorphism of a group to the model of transformation from
physical structures to the psychological originated from Jean Piaget. How
ever, Jean Piaget has not given a mathematic expression by which the
psychological phenomena can be represented, and he has not taking the model
as the common model of consciousness. In the paper, the homomorphic model of
consciousness is given in a mathematic expression, by which the some
important questions relevant to the consciousness are formalized and the
answer can be acquired, the questions (with the followed answer solved by the
homomorphic model of consciousness) are Chinese room argument, Turing machine
question, Turing Test question, and about if animals have consciousness, in
what the meaning of utilizing and making tools lies, if DNA and protein
system have consciousness. And finally the paper concludes that consciousness
exists when : (1) the units of system certainly map the entities outside the
system; (2) the system operate by some rules; and (3) the rules certainly map
some laws or relations in the entities. The essence of consciousness is certain
correspondence between substance with some rules or laws.” ************************************************** Book reivew: Consciousness
Reconsidered by Owen Flanagan (The MIT Press. 1992) SIGART
Bulletin , Volume 4 Issue 3, July 1993 Publisher: ACM
Abstract “Design
and manufacturing play a crucial role in the wealth creation of nations and
their use of computer technology forms an important element in the process.
Much has been written on the application of AI to design and manufacturing
[1,2,3,5,7] in which AI has been touted to be able to increase the
effectiveness and sophistication of computer applications in these areas.” Full text available: Pdf ACM (603.47
KB) http://www.fgalindosoria.org/eac/conciencia/ ************************************************** |
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