Logic 2 - First-order Logic | Stanford CS221: AI (Autumn 2019)

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: stanford.io/3b...
Topics: First-order Logic
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor - Stanford University
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Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
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Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
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To follow along with the course schedule and syllabus, visit:
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[@joker345172]

This is much better than the material supplied by my university's AI class! I learned more about the topic after 5 minutes of this video than after 2 entire 2-hour lectures by my professor. Thank you so much!

[@LusantisuperBR]

Yeah man, don't tell me. Are you that smart guy from my class?

[@neoblackcyptron]

These courses are excellent, they really supplement and add to the material we cover at my university in our intro to AI class. If any topics is unclear in the class, these set of excellent lectures really help clear them all up. Thanks for these series of lectures. I will have to watch them all from the beginning.

[@williamofdallas]

Lecture begins at 9:06

[@TruthNerds]

"We know that 3-SAT is a very hard problem."
We do? Well, some of the most brilliant minds of our time have tried to come up with an efficient solution and have not succeeded. In that sense, we know that it's a very hard problem.
What we do not know is whether 3-SAT is necessarily computationally hard. 3-SAT (like the more general SAT) is NP-complete. This means that _if_ anybody were to come up with a deterministic polynomial time algorithm that solves 3-SAT, then _all_ NP-complete problems are also solvable in deterministic polynomial time and P=NP.
Most researchers strongly believe that P is not equal to NP and therefore do not expect to ever learn of such an algorithm.
Also note that P ≠ NP does not imply that the best deterministic algorithm for NP-complete problems is exponential, it only means that it's superpolynomial i.e. not O(n^k) for any k.
Pedantic maybe but confusion regarding the P=NP question abounds so one can hardly use overly precise wording.

[@brainstormingsharing1309]

Absolutely well done and definitely keep it up!!! 👍👍👍👍👍

[@hendrixbrysen9433]

Instablaster...

[@joshuabonroco7055]

Anyone here who can recommend additional reading material for this topic? I just need more examples.

[@hey.guitarbjorn]

Rosen: Discrete mathematics
Norvig: Artificial Intelligence: A Modern Approach

[@ZeliWipin]

thank you for this

[@afanoromolyricsofficial]

great lecture

[@brainstormingsharing1309]

👍👍👍👍👍

[@moondir]

∃x(L(x)∧∃y(M(y)∧F(x,y)∧thank(x)))
L(x) represent "x liked the lecture,"
M(y) represents "y is a movie," and
F(x,y) represent "x felt like watching y"
thank(x) as "x expresses thanks"