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Explanation-based Learning and New Ideas About AI

Explanation-based Learning and New Ideas About AI. Yin Wang, Shiliang Sun, Naveed. Prolog-EBG---Evaluation. Prolog-EBG can be viewed as an enhanced version of Find-S Both consider only positive examples Every hypothesis in Find-S can be expressed by a conjunction of clauses in Prolog-EBG. ?.

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Explanation-based Learning and New Ideas About AI

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  1. Explanation-based Learning and New Ideas About AI Yin Wang, Shiliang Sun, Naveed

  2. Prolog-EBG---Evaluation • Prolog-EBG can be viewed as an enhanced version of Find-S • Both consider only positive examples • Every hypothesis in Find-S can be expressed by a conjunction of clauses in Prolog-EBG

  3. ? generalize Version Space Analog How can the negative examples be useful ? • Find-S : Candidate-Elimination = Prolog-EBG : ?

  4. What type of logic is this clause? Knowledge-level Learning • IF ((PlayTennis = Yes)  (Humidity = x)) THEN ((PlayTennis = Yes)  (Humidity <= x )) • Example: (Humidity = .30 and PlayTennis = Yes) • New hypothesis: (PlayTennis = Yes)  (Humidity <= 0.30 ) • Input of example into domain theory by means of Abstraction (Here the variable is x)

  5. Alternative Preimage Structures • The space of preimage will become large for some problems • The need for fast rule-matching algorithms and new representations • Can the rules be represented as a hierachical structure which goes down only into certain level footimage ?

  6. How should the rules be structured for matching ? Example • SafeToStack(x,y)  Volume(x) * Density(x) < 5 and Type(y, Endtable) • Too specific ? • Is SafeToStack(x,y)  Weight(x) < Weight(y) enough ? (We have a balance?) • Restrict the reasoning in a reasonable level. Don’t go too much into details !

  7. Evaluation of The Second Paper • Can be useful for understanding human intelligence • Maybe useful for AI in the future • GOD is a far better engineer than us • Can mechanical things have intelligence? Philosophy or religion ?

  8. Symbol vs. Concept Intuition ? • Symbol is NOT Concept • Concept involves more than symbols • Sporadic memory of sensory signals (How to represent them ?) • Personal history of the concept ( non-intentional memory? People remember much more than symbols ! ) • Without feelings and non-intentional memory, there will be no true intelligence

  9. Muscle Memory • Memory in the motor system is not restricted in the brain • Motor system of the machine should have something like the muscle memory, rather than all computed by the CPU • Dancing • Martial-arts • …

  10. The Right-side Brain • How can a machine imitate the parallel processing of the right side brain ? • Need a restructurable processor ?

  11. Give the Machine the desire for truth? Emotional Thinking How can a machine have desire ? What is desire ? • All previous models are based on rational thinking • True living human have more • I Think • I Feel • I Desire • Let the learning process be desire-driven !

  12. More Mental Abilities • Sympathy • Imagination • Creativity

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