Confabulation Theory: The Mechanism of Thought

1. Confabulation Theory:The 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(ε|αβγδ) • Wrong model • Alternate model : Cogency : p(αβγδ|ε) • α,β,γ,δ : Assumed facts • ε : Conclusion

21. Cogency Theorems • Thm 1: If αβγδ => ε exclusively, then maximization of cogency produces one and only one answer ε • Aristotelian logic information environment: maximizing cogency gives logical answers

22. Cogency Theorems • Cogency calculation : only in trivial situations • Confabulation Product : p(α|ε).p(β|ε).p(γ|ε).p(δ|ε) • Thm 2: [p(αβγδ|ε)]4 = [p(αβγδε)/p(αε)].[p(αβγδε)/p(βε)]. [p(αβγδε)/p(γε)].[p(αβγδε)/p(δε)]. [p(α|ε).p(β|ε).p(γ|ε).p(δ|ε)] • In non-exceptional cases, [p(αβγδ|ε)]4≈C*[p(α|ε).p(β|ε).p(γ|ε).p(δ|ε)]

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 Baye’s Law? • p(λ)=0.01; p(ε)=0.0001; p(αβγδ|λ)=0.01; p(αβγδ|ε)=0.2 • p(αβγδ|ε)= 20 * p(αβγδ|λ) • p(λ |αβγδ)= 5 * p(ε|αβγδ) • Baye’s Law => λ • Cogency => ε

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 Baye’s Law? • Typical answers : • Naps • Happy • Wondering • Wood • Fun • ‘the’ also viable : Baye’s 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