On database keys, with an application to the Praxisproblem Derek J' SMITH Centre for Psychology Univ

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On database keys, with an application to the
PraxisproblemDerek J. SMITHCentre for
PsychologyUniversity of Wales Institute,
Cardiffdsmith_at_uwic.ac.ukhttp//www.smithsrisca.
demon.co.uk

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As presented to the9th World Multi-Conferenceon
Systemics, Cybernetics, and InformaticsOrlando,
FL, Tuesday 12th July 2005

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A BIT MORE ABOUT THE AUTHOR

• 1980s - specialized in the design and operation
  of very large IDMS databases.
• Since 1991 taught cognitive science and
  neuropsychology to Speech and Language
  Pathologists.
• Hence interdisciplinary in database, cognitive
  neuropsychology, and psycholinguistics.
• Hence fascinated by the possibility that the mind
  is a biological database capable of linguistic
  communication.

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DEFINITIONS (1)VOLITION AND PRAXIS

• Volition is the exercise of the Will.
• Praxis comes from the Greek prassein, "to do,
  and refers generally to a systems ability to
  initiate voluntary physical behavior of any sort
  (hence we call it dyspraxia when something goes
  wrong).
• Speech praxis is the process by which the Will
  voluntarily initiates the expression of a given
  idea though the medium of spoken language.

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DEFINITIONS (2)REDUCTIONISM

• Reductionism is explaining complex phenomena in
  terms of their parts. E.g. how nuts, bolts, etc.,
  make an automobile.
• However, theres a big problem with reductionist
  explanations, because systems are frequently
  greater than the sums of their parts, and you
  lose much of their essence as soon as you start
  taking them apart. This is especially true of the
  mind, which seems to be massively more than the
  sum of its neurons.
• Following Levine (1983), we favor the term
  Explanatory Gap for this problem.

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PLAN OF ATTACK

• This paper looks at the explanatory gap problem
  in speech praxis, and shows how that gap might be
  narrowed in an artificial cognitive system using
  CODASYL-style database keys.
• This means bringing together two hitherto
  unconnected areas of knowledge, so we shall open
  with background" sections on (a) the
  psycholinguistics of speech praxis, and (b) the
  use of database keys in CODASYL databases. Well
  then present a pseudocode demonstration of how
  the one can help the other.

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Well also be telling you a little about what
went on at this place a while back.
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LORDAT (1843)FIVE STAGES OF SPEECH
PRAXIShttp//www.smithsrisca.demon.co.uk/PSYlorda
t1843.html

• So what do psycholinguists know about speech
  praxis?
• Well in 1843 the French neurologist Jacques
  Lordat identified five processing stages within
  speech production, and described the first of
  these as isolating the idea to be expressed in
  words.
• The four subsequent processes then co-operate in
  shaping the final spoken output, as now shown ..

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LORDAT (1843)

• Each stage receives a coded message from the one
  before, adds to it in some clever way, and then
  passes it on to the one after.

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LORDAT (1843)FIVE STAGES OF SPEECH PRAXIS

• Lordats explanation was duly incorporated into a
  number of later 19th century aphasiological
  models, and is worth noting because in one form
  or another it is still with us today.
• The explanatory diagrams are typically either
  A-shaped (with the clever bits the minds
  higher functions - at the top) or X-shaped
  (with the clever bits at the central cross-over
  point). Here are two of the A-shaped ones, one
  old and one new ..

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LICHTHEIM (1885)TWO-LAYER CONTROL
HIERARCHYhttp//www.smithsrisca.demon.co.uk/PSYli
chtheim1885.html
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NORMAN (1990)MODERN THREE-LAYER
HIERARCHYhttp//www.smithsrisca.demon.co.uk/PSYno
rman1990.html
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MODERN SPEECH PRODUCTION MODELS

• Speech production did not become a popular study
  topic until 1971, when Fromkin's "Utterance
  Generator" model extended Lordat from five stages
  to six.
• The most popular modern models of speech
  production come from the Max Planck Institute's
  Willem Levelt and the University of Arizona's
  Merrill F. Garrett. But they all take the same
  basic shape, so well work for now with Fromkins
  ..

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FROMKINS FIRST THREE STAGES

• Stage 1 Pre-Lexical Semantics Decides the
  meaning to be conveyed. Code not known, but
  preverbal.
• Stage 2 Pre-Lexical Syntax Decides the
  grammatical skeleton of the sentence. Code not
  known, but preverbal.
• Stage 3 Lexical Selects the necessary content
  words (i.e. nouns and verbs) from the mental
  lexicon, thus making ideas verbal for the first
  time.
• Its worth remembering these three stages as a
  unit, because well be returning to them later.

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FROMKINS LAST THREE STAGES

• Stage 4 Prosody Adds in emotionality via
  intonation pattern. Code not known, but mediated
  by the hindbrain.
• Stage 5 Phonology Decides the final syntax and
  word morphology. Phonemic code.
• Stage 6 - Final Sound Production Commits
  concrete sounds - "allophones to the motor
  nerves for respiration, phonation, and
  articulation.
• Were not really concerned with these three
  stages in this paper, because they are all
  post-semantic.

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BUT ARE PROCESSING STAGES THE SAME AS MODULAR
LAYERS?

• Theres another big problem here, because
  Fromkin's six stages do not necessarily map onto
  six CPUs each running a single computer program.
  The diagrams we saw just now are all showing
  processors physical modules - not processing
  stages.
• In fact, its a many-to-many relationship. You
  can fit Fromkin's six stages perfectly into
  Lichtheim's two physical processing modules if
  only you bundle them properly! This many-to-many
  cross-mapping has never been properly resolved,
  and is still a major source of mis-understanding
  and confusion within Artificial Intelligence.

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STATE-OF-THE-ARTPSYCHOLINGUISTIC MODELING

• The PALPA (Kay, Lesser, and Coltheart, 1992) is a
  typical X-shaped psycholinguistic diagram (that
  is to say, the Will is located in the middle of
  the diagram, not at the top).
• Here it is ..

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The PALPAhttp//www.smithsrisca.demon.co.uk/PSYka
yetal1992.html

• All input channels are now at the top, and all
  output channels at the bottom. Ideation is in the
  centre box, and speech praxis is the bottom left
  processing leg.
• Our question is, how do ideas make it out of the
  centre box and down the first arrow!

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SPEECH ACTS AND IDEATION (1)

• In fact, praxis is so complex that it has its own
  science pragmatics ..
• .. and its own very powerful theory - Speech Act
  Theory (Austin, 1962 Searle, 1969). Speech Act
  Theory studies not just the words people use, but
  the units of intention the speech acts which
  preceded those words.
• Pragmatics is thus the science of the centre box
  and the first arrow ..

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SPEECH ACTS AND IDEATION (2)

• Each speech act is (a) calculated to achieve some
  discrete behavioral "perlocutionary" effect, but
  (b) has not yet been fully formed lexically or
  grammatically.
• The code is preverbal - perhaps sprites or
  ideograms of some sort.
• Speech acts havent been very well modeled yet,
  and so remain poorly understood (although we hope
  to start the ball rolling with this paper).

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SPEECH ACTS AND IDEATION (3)

• Speech Act Theory has its own very difficult
  jargon. In this paper, for example, we shall be
  hearing about a directive speech act, with a
  requestive subtype, invoking the core verb to
  summons.
• The mind has about a 1000 different speech acts
  to choose from (more details in Bach and Harnish,
  1979).

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ANIMATED PALPA SMITH (2000)

• So what might a speech act look like? Where do
  these all-important sprites come from, where do
  they go, and what happens to them when they get
  there?
• To get a better idea of the process, we need to
  see the static flow diagram in motion. So here,
  from Smith (2000), is sentence production more or
  less in real time, for the specimen sentence The
  Redcoats are coming ..

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(No Transcript)
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(No Transcript)
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OUR BASIC PROPOSAL

• So how might a network database help?
• Well above all it would help demonstrate how
  mental content is progressively accessed during
  sentence production. Not just ideation and
  initiation (Stages 1 and 2), but lexical
  expansion (Stage 3) as well.
• Heres some important background (weve taken
  Computer Associates' IDMS system, a 1969 network
  database, as the class-defining CODASYL database)
  ..

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ABOUT NETWORK DATABASES (1)IDMS DATABASE KEYS

• Data is organized into "records.
• Filestore is organized into block-sized "pages
  of up to 256 records per page.
• The resulting page-line address is known as the
  "database key" for that record.

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ABOUT NETWORK DATABASES (2)IDMS DIRECT ACCESS

• IDMS is a supremely flexible data retrieval tool.
  It offers 10 ways of finding things, the most
  fundamental of which is direct access. Just like
  the brain during every act of perception.

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ABOUT NETWORK DATABASES (3)IDMS DIRECT ACCESS

• A hashing algorithm computes the page number from
  the logical record key (Dumey, 1956).
• Once a record has been located, its database key
  is automatically stored by the DBMS as a
  currency.

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ABOUT NETWORK DATABASES (4)CHAIN POINTER ACCESS

• IDMS also arranges for certain data records to
  "own" certain others, thus capitalizing on the
  data's natural one-to-many "set" relationships.

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ABOUT NETWORK DATABASES (5)CHAIN POINTER ACCESS

• Each record includes in its physical record
  length the database key of the next record in
  that set. These chain pointers are a storage
  overhead, but one which is well worth paying.
  Just like the brain during semantic or lexical
  categorization.

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ABOUT NETWORK DATABASES (6)CURRENT OF SET
ACCESS

• Once a record has been located, its database key
  is automatically stored by the DBMS, identifying
  it as current of set for the set in question.
• This makes said record effectively direct
  access, even if it had originally taken a lot of
  chain pointering to track down. Just like the
  brain during medium term recall.

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ABOUT NETWORK DATABASES (7)IDMS TRAVERSALS

• In practice, the final outputs of a database
  interrogation are always composites of fragments
  of data collected from potentially hundreds of
  points across the network. The process of
  collecting these fragments is known as
  traversing the database. The inventor of the
  process, Charles W. Bachman, winner of the 1973
  A.C.M. Turing Award, once likened it to
  "navigating" (Bachman, 1973).
• Traversals are hard to plan, but then easy to
  achieve using only a handful of "Data
  Manipulation Language" (DML) verbs, such as
  OBTAIN CALC, OBTAIN NEXT, MODIFY, and ERASE.

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TOWARDS AN IDMS "MINDBASE" (1)DATABASE KEYS AND
MACHINE VOLITION

• OK, so lets start to bring these thoughts
  together ..
• Supposing the mind were an IDMS database, then
  for database traversal purposes, only the first
  three of Fromkin's six stages would need to be
  considered. This is because they are the ones
  which access the semantic network. Everything
  else is just number-crunching.
• Lets look at those stages one by one ..

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TOWARDS AN IDMS "MINDBASE" (2)ISOLATING A
PROPOSITION

• Stage 1 is where we tap into the minds central
  stream of contextually coherent propositional
  thought.
• Each successive proposition will activate a
  number of the mental sprites we have been talking
  about. Always ltagentgt and ltactiongt, and sometimes
  also ltobjectgt, ltadverbialgt, and ltinstrumentalgt.
• Every now and then, a small subset of
  propositions becomes salient enough to warrant
  initiating a communicative act, whereupon that
  particular unit of ideation is "isolated" ready
  for production.

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TOWARDS AN IDMS "MINDBASE" (3)SPEECH ACT
SELECTION

• Stage 2 is responsible for converting the
  afore-mentioned subset of propositions into a
  speech act of some sort.
• The point is that by selecting a particular
  speech act, we restrict our choice of possible
  sentence structures to only a handful of options.
  It is rather like opening sealed orders on a
  military mission - one specific action gets
  selected from a repertoire of many, you get told
  what to do next, and the desired outcomes are
  specified.

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TOWARDS AN IDMS "MINDBASE" (4)LEXICAL EXPANSION

• Stage 3 is where we start attaching words to
  what until now have been preverbal codes.
• Unfortunately, this process does not always work
  cleanly see our e-paper on Speech Errors at
  www.smithsrisca. demon.co.uk/speech-errors.html.

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TOWARDS AN IDMS "MINDBASE" (5)STAGES 1 TO 3 IN
PSEUDOCODE

• Here are some extracts from the pseudocode set
  out in the written version of this presentation.
  The selections show the following four
  circumstances ..
• (1) Isolation of ideation.
• (2) Selection of a speech act by direct access.
• (3) Chain pointer use in opening a set.
• (4) Set currency use in continuing a set.

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INDICATIVE IDMS PSEUDOCODE (1)ISOLATING PAUL
REVERES IDEA

• Different combinations of external circumstances
  demand different actions ..
• IF AGENT .
• .
• ELSE IF AGENT BRITISH COLUMN
• IF ACTION On null condition ..
• NEXT-SENTENCE .. no action is necessary
• ELSE IF ACTION MOVING NORTHWEST
• MOVE PLAN X TO SPEECH-ACT-CODE
• NEXT SENTENCE
• ELSE IF .
• ELSE IF .
• .....

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INDICATIVE IDMS PSEUDOCODE (2) EXAMPLE OF DIRECT
ACCESS

• Once a given set of circumstances has prompted a
  particular pre-learned plan of action, the
  detailed response can be retrieved from long-term
  memory ..
• MOVE SPEECH-ACT-CODE TO ACT-RECORD-KEY.
• OBTAIN CALC ACT-CONTROL-RECORD.
• The sealed orders on this occasion specify a
  directive speech act, with a requestive
  subtype, and the core verb to summons.

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INDICATIVE IDMS PSEUDOCODE (3) EXAMPLE OF CHAIN
POINTER ACCESS

• The waypoints on the road to Lexington are
  themselves in long-term memory, organized on an
  owner/member set basis ..
• MOVE MIDDLESEX COUNTY TO DISTRICT-KEY.
• OBTAIN CALC DISTRICT. We dont actually need this
  record, but we have to get it because it contains
  the chain pointer to the first set member ..
• OBTAIN FIRST MINUTEMAN IN MINUTEMEN-IN-DISTRICT.

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INDICATIVE IDMS PSEUDOCODE (4) EXAMPLE OF SET
CURRENCY USE

• Having processed one minuteman, we have to
  relocate its record before getting the next,
  again because we need the chain pointer it
  contains ..
• OBTAIN CURRENT MINUTEMAN.
• OBTAIN NEXT MINUTEMAN IN MINUTEMEN-IN-DISTRICT.

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CONCLUSION (1)WHAT WE HAVE SEEN SO FAR

• This has been no more than a first foray into the
  explanatory gap, in an attempt to redefine the
  philosophical problems of biological cognition as
  network database problems.
• The pseudocode is entirely typical of IDMS
  programming, in that you have to pay precise
  attention (a) to where you are in the data
  network, and (b) to how you are going to get to
  where you want to be next. The record and set
  currency mechanisms are invaluable in this
  respect.
• We may identify three specific potential
  advantages of the IDMS metaphor ..

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CONCLUSION (2)IDMS IS LIKE FOR LIKE WITH BIOLOGY

• The network database is just that, a network, and
  so, too, is biological associative memory.
• And yet only a microscopic proportion of the
  billions spent on AI in the past 50 years has
  utilized a physical network architecture.

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CONCLUSION (3)IDMS IS TOTALLY REDUCIBLE

• The activity of an IDMS mindbase is automatically
  totally reducible. The DML is pre-processed to
  native COBOL, and then put through the regular
  COBOL compiler to produce object code. Both
  conversions are 100 trackable, and in debug mode
  we can even execute the object code one
  instruction at a time.
• This is important because what cognitive
  theorists are really about is reverse engineering
  - de-compiling neural object code in order to
  understand what on earth it is up to.

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CONCLUSION (4)IDMS MIMICS NEUROCHEMISTRY

• IDMS's use of database currencies is uncannily
  similar to the brain's physiological memory
  mechanisms. E.g. second messenger
  neurotransmission and calcium switching. In
  other words, biological long-term memory looks to
  have its own keys and currencies (Smith, 1997).
• Or to put it another way, closing the explanatory
  gap is a code-breaking exercise of sorts!

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CONCLUSION (5)CRYPTANALYSIS IN COGNITIVE SCIENCE

• The building we saw earlier was Station X
  Bletchley Park The UK Code and Cipher School
  during World War Two, where Alan Turing helped
  decode the Nazi Enigma signal system ..

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CONCLUSION (6)THE COLOSSUS

• .. and the birthplace in December 1943 of the
  worlds first programmable electronic binary
  digital computer.

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CONCLUSION (7)THE COLOSSUS BUILDING

• .. which was successfully rebuilt by
  preservation enthusiasts between 1994 and 1996.

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CONCLUSION (8)TURINGS OFFICE (HUT 8) NOWADAYS

• The same Alan Turing, incidentally, who inspired
  the A.C.M. Turing Award, saw the mind as
  computable, and devised the Turing Test of
  machine consciousness.

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CONCLUSION (9)SPECIFIC PROPOSAL

• The best way across the explanatory gap would be
  to approach it as a code-breaking exercise,
  starting with neural crackle as the given
  intercept, and reverse engineering it back to
  the DML of the original ideation ..
• .. and looking out especially for the location
  of the biological currency tables.
• IDMS may even assist students of artificial
  consciousness at the same time ..

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CONCLUSION (10)ARTIFICIAL CONSCIOUSNESS

• A leading consciousness theorist, David Chalmers,
  has argued that if a technically advanced theory
  could one day explain at the reductionist level
  how the brain thinks, it would still be "silent
  about how these processes might give rise to
  conscious experience" (Chalmers, 1995, p64).
• We submit IDMS as a candidate for Chalmers'
  "technically advanced theory ..
• .. and suspect that its reducibility and
  capacity for slow motion execution will reflect
  on the how question as well.

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THE END

• Or is it??

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REFERENCES

• Austin, J.L. (1962). How to do Things with Words.
  Oxford Oxford University Press.
• Bach, K. and Harnish, R.M. (1979). Linguistic
  Communication and Speech Acts. Cambridge, MA
  MIT Press.
• Chalmers, D.J. (1995). The puzzle of conscious
  experience. Scientific American, 273(6)62-68.
  Levine (1983)
• Fromkin, V.A. (1971). The non-anomalous nature of
  anomalous utterances. Language, Vol. 47, pp.
  27-52.
• Searle, J.R. (1969). Speech Acts An Essay in the
  Philosophy of Language. Cambridge Cambridge
  University Press.
• Smith, D.J. (1997). The IDMS Set Currency and
  Biological Memory. Cardiff UWIC. ISBN
  1900666057
• Smith, D.J. (2000). A slow-motion video analysis
  of information feedback in a computer-animated
  psycholinguistic model. Computer-animated poster
  presented 10th April 2000 at the Tucson 2000 -
  Towards a Science of Consciousness conference,
  University of Arizona, Tucson, AZ. Available
  online at http//www.uwic.ac.uk/shss/djs/palpa.avi