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

4. 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) What type of logic is this clause?

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. 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 ! Example How should the rules be structured for matching ?

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 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 Intuition ?

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. Emotional Thinking 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 ! How can a machine have desire ? What is desire ? Give the Machine the desire for truth?

12. More Mental Abilities Sympathy Imagination Creativity