CS661 Artifical Intelligence
Lecture 4 - Complexity, Godel's theorem, the Halting problem
- Complexity
- Bandersnatch problem (Garey and Johnson)
- problems can be :
- easy (polynomial)
- NP-hard
- truly hard (provably non-polynomial, exponential)
- impossible
- Decision problems (problems with yes/no answers) can be :
- P (problems with poly-time Turing solution)
- NP (can test solution in poly time, so can guess and test)
- NP-complete (hardest problems in NP)
- truly hard (must try all combinations)
- Reduction of problems (if can solve A can certainly solve B)
- Does P=NP? (drawing of world of problems) unknown!
- Examples of NP-complete problems: TSP, SAT, knapsack
- All of the above is worst case analysis, average case may be easy!
- Godel's theorem and the Halting problem
- Russels’s paradox: barber paradox, Epimedes “I am lying”
- Goldbach conjecture (every even>4 = sum of two primes) vs. difference of two primes
- Examples: always, never, sometimes, sometimes2, looper, who_knows Pascal code
- use of string representation (Godel - numeric coding)
- proof that halts function does not exist Pascal code
- Godel’s theorem (every sufficiently strong axiom system has non-provable true theora)
- Eliminating Russel’s paradox from axiomatic set theory
- Principia Mathematicia - all math based on set theory
- Do we know any Godelean problems (FLT, Goldbach, P=NP)?