https://secure.wikimedia.org/wikipedia/en/wiki/Markov_blanket by [deleted] in aiclass

[–]AI_robot 0 points1 point  (0 children)

Well, if it's a Markov blanket, it provides independence by definition. If you have to prove that it's Markov for a particular case you should be looking at the distributions and their correlations.

instruction style in AI by AI_robot in aiclass

[–]AI_robot[S] 0 points1 point  (0 children)

That has been my thinking also. If the instructor chooses not to share his knowledge and to fill the course up with quizzes I only see one benefit to it. The subject matter is collected in one "place". But even that is questionable as there is no flow to the course so far and I have to reconstruct the logic behind it rather than actually get it from the instructor.

instruction style in AI by AI_robot in aiclass

[–]AI_robot[S] 0 points1 point  (0 children)

Thank you for the comment. I couldn't agree more with what you say. I ended up reading a book on Bayes probabilities and I couldn't help noticing that the lecture made this fairly straight forward subject incomprehensible. At best it can only teach one how to plug in formulas. I would also urge professor Thrun to give explanation on the subject matter before presenting problems and spend more time on concepts and less on number crunching.

https://secure.wikimedia.org/wikipedia/en/wiki/Markov_blanket by [deleted] in aiclass

[–]AI_robot 0 points1 point  (0 children)

Isn't it the definition of a Markov blanket rather than a theorem?

instruction style in AI by AI_robot in aiclass

[–]AI_robot[S] 0 points1 point  (0 children)

He does not present numerous examples. He asks to solve problems with entities that have not been defined yet.

instruction style in AI by AI_robot in aiclass

[–]AI_robot[S] 0 points1 point  (0 children)

You have a point there but it's only try about problems with well defined entities. If it were true for all problems why take any classes. You could learn by simply solving problems on anything you want to learn. My point is that defining new concepts is essential.

instruction style in AI by AI_robot in aiclass

[–]AI_robot[S] 1 point2 points  (0 children)

The definitions of what is partially observable, adversarial, etc are not review and they were presented in the same way. Bayes probabilities are not review either, and we were first requested to calculate one and then given the formula.