 
 
 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)? 
 
 
