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Confabulation Theory: The Mechanism of Thought

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Title: Confabulation Theory: The Mechanism of Thought


1
Confabulation TheoryThe Mechanism of Thought
  • Group-7

2
Mental World
3
What is Cognition?
  • Cognition
  • Understanding and trying to make sense of the
    world
  • Information processing
  • Development of concepts
  • The mental functions, mental processes and states
    of intelligent entities with focus on
  • comprehension,
  • inference,
  • decision-making,
  • planning and
  • learning etc.

4
Cognition
  • Cerebral Cortex
  • Seat for cognition
  • How is Cerebral cortex able to do what it is able
    to do?
  • Fuzzy explanations
  • No clear cut perspective in exact terms
  • Introducing Confabulation Theory
  • A discrete insight into possible mechanism of
    thought

5
Confabulation Theory
  • Proposed by Robert Hecht-Nielson
  • All human cognition and behavior based on one
    simple, non-algorithmic procedure that has been
    named confabulation
  • All aspects of cognition carried out using
  • a single type of knowledge and
  • a single information processing operation called
    (confabulation)

6
Relevance
  • Radical novel approach
  • First-of-its-kind concrete model
  • Issuing deeper insights into process of cognition
  • Augmenting present
  • Artificial intelligence
  • knowledge discovery
  • knowledge management

7
Roadmap
  • Cognitive World Object Representation
  • Knowledge Links
  • Confabulation
  • The Mathematics of Cogent Confabulation
  • The Origin of Behaviour
  • Conclusion

8
Cognitive World Object Representation
  • Cerebral Cortex
  • 4000 discrete, localized, disjoint patches
  • Thalamocortical Module
  • cortical patch and first-order thalamic zone
    uniquely paired by reciprocal axonal
    interconnection
  • Module
  • one attribute of an object of mental world

9
Cognitive World Object Representation
10
Cognitive World Object Representation
  • How are these modules used?
  • Make groups of 60 symbols
  • Module may consist of thousands of neurons
  • Symbol one possible descriptor of an attribute
  • One neuron may belong to more than one symbols
  • Symbols have to be permanent

11
Cognitive World Object Representation
12
What is Knowledge?
  • Knowledge accumulates in discrete units
  • Knowledge link or knowledge unit is an axonal
    linkage between source symbol and target symbol
  • Source and target symbols belong to different
    modules

13
Knowledge Links
14
Formation of knowledge links
  • Two symbols become co-active to send out signals
  • Synapses are strengthened in the process of
    learning
  • Permanent strengthening during sleep
  • Billions of knowledge links
  • Humans and animals are 'smart

15
Confabulation
  • One and only one information processing operation
  • Localized
  • Winners-take-all
  • Symbol with highest total knowledge link input is
    conclusion of confabulation

16
Implications of Knowledge Link
  • Source symbol neurons send signals to millions of
    transponder neurons
  • Only few thousand transponder neurons become
    highly excited
  • 10 of the target neurons receive signals from
    multiple transponder neurons

17
Implications of Knowledge Link
18
Confabulation Neuron Level
19
Cogency
20
Cogency
  • Aristotelian model An appealing model for
    cognition p(eaß?d)
  • Wrong model
  • Alternate model Cogency p(aß?de)
  • a,ß,?,d Assumed facts
  • e Conclusion

21
Cogency Theorems
  • Thm 1 If aß?d gt e exclusively, then
    maximization of cogency produces one and only one
    answer e
  • Aristotelian logic information environment
    maximizing cogency gives logical answers

22
Cogency Theorems
  • Cogency calculation only in trivial situations
  • Confabulation Product p(ae).p(ße).p(?e).p(de
    )
  • Thm 2 p(aß?de)4
  • p(aß?de)/p(ae).p(aß?de)/p(ße).
    p(aß?de)/p(?e).p(aß?de)/p(de).
    p(ae).p(ße).p(?e).p(de)
  • In non-exceptional cases, p(aß?de)4Cp(ae).p
    (ße).p(?e).p(de)

23
Confabulation Examples
  • Some examples from test
  • She could determine (whether, exactly, if, why)
  • If it was not (immediately, clear, enough, true)
  • Earthquake activity was centered
  • For lack of a (unified, blockbuster,
    comprehensive, definitive)
  • A lack of (urgency, oxygen, understanding)
  • Regardless of expected outcome, length
  • Automatic emergence of semantics and grammar

24
Why Cogency and not Bayes Law?
  • p(?)0.01 p(e)0.0001 p(aß?d?)0.01
    p(aß?de)0.2
  • p(aß?de) 20 p(aß?d?)
  • p(? aß?d) 5 p(eaß?d)
  • Bayes Law gt ?
  • Cogency gt e

25
Quiz! (For those who are sleeping)
  • Quickly select a next word for each of the
    following
  • Company rules forbid taking
  • Mickey and Minnie were
  • Capitol hill observers are
  • Paper is made from
  • Riding the carousel was

26
Why Cogency and not Bayes Law?
  • Typical answers
  • Naps
  • Happy
  • Wondering
  • Wood
  • Fun
  • the also viable Bayes law

27
Conclusion-Action Principle Origin of Behavior
28
Conclusion-Action Principle Origin of Behavior
  • Every time a confabulation operation on a module
    reaches a conclusion, an associated set of action
    commands are launched
  • Winner of a confabulation competition employs
    skill knowledge to launch an action
  • Skill knowledge, and skill learning are not parts
    of cognitive thinking

29
Hindering Blocks
  • Conceiving and then precisely defining a
    confabulation architecture
  • Conceiving and then precisely defining the
    thought processes
  • Conceiving and executing an appropriately staged
    sequence of learning opportunities

30
Conclusion
  • A new dimension to the mechanism of thought
  • Based on Cogency (refutes Bayesian model)
  • If proved correct
  • Better insight into human cognition
  • Will redefine the outlook towards various AI
    problems
  • Radical improvement in present ML techniques

31
References
  • Robert Hecht-Nielson, Cogent Confabulation,
    Neural Networks Letter, 2004
  • Robert Hecht-Nielson, Confabulation Theory A
    Synopsis, Institute for Neural Computation, 2005
  • Robert Hecht-Nielson, The Mechanism of Thought,
    International Joint Conference on Neural
    Networks, 2006
  • scholarpedia.org/confabulation

32
ThanQ
  • Animal cognition maximizes cogency, and in a
    non-logic environment, cogency maximization
    implements what I call the duck test." - Robert
    Hecht-Nielson
  • There must be some event that triggers every
    behavioral event, and it had to be the same in
    every instance, whether we're thinking, moving,
    or whatever." - Robert Hecht-Nielson
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