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Lecture 23: Intractable Problems (Smiley Puzzles and Curing Cancer). David Evans http://www.cs.virginia.edu/evans. CS200: Computer Science University of Virginia Computer Science. Menu. Review: P and NP NP Problems NP-Complete Problems. Complexity Class P. - PowerPoint PPT Presentation
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David Evanshttp://www.cs.virginia.edu/evans
CS200: Computer ScienceUniversity of VirginiaComputer Science
Lecture 23: Intractable Problems(Smiley Puzzles and Curing Cancer)
21 March 2003 CS 200 Spring 2003 2
Menu
• Review: P and NP
• NP Problems
• NP-Complete Problems
21 March 2003 CS 200 Spring 2003 3
Complexity Class P
Class P: problems that can be solved in polynomial time
O(nk) for some constant k.
Easy problems like sorting, making a photomosaic using duplicate tiles, understanding the universe.
21 March 2003 CS 200 Spring 2003 4
Complexity Class NP
Class NP: problems that can be solved in nondeterministic polynomial time
If we could try all possible solutions at once, we could identify the solution in polynomial time.
We’ll see a few examples today.
21 March 2003 CS 200 Spring 2003 5
Why O(2n) work is “intractable”
1
100
10000
1E+06
1E+08
1E+10
1E+12
1E+14
1E+16
1E+18
1E+20
1E+22
1E+24
1E+26
1E+28
1E+30
2 4 8 16 32 64 128
n! 2n
n2
n log n
today2022
time since “Big Bang”
log-log scale
21 March 2003 CS 200 Spring 2003 6
Smileys Problem
Input: n square tiles
Output: Arrangement of the tiles in a square, where the colors and shapes match up, or “no, its impossible”.
21 March 2003 CS 200 Spring 2003 8
How much work is the Smiley’s Problem?
• Upper bound: (O)O (n!)
Try all possible permutations
• Lower bound: () (n)
Must at least look at every tile
• Tight bound: ()
No one knows!
21 March 2003 CS 200 Spring 2003 9
NP Problems
• Can be solved by just trying all possible answers until we find one that is right
• Easy to quickly check if an answer is right – Checking an answer is in P
• The smileys problem is in NPWe can easily try n! different answers
We can quickly check if a guess is correct (check all n tiles)
21 March 2003 CS 200 Spring 2003 10
Is the Smiley’s Problem in P?
No one knows!
We can’t find a O(nk) solution.
We can’t prove one doesn’t exist.
21 March 2003 CS 200 Spring 2003 11
This makes a huge difference!
1
100
10000
1E+06
1E+08
1E+10
1E+12
1E+14
1E+16
1E+18
1E+20
1E+22
1E+24
1E+26
1E+28
1E+30
2 4 8 16 32 64 128
n! 2n
n2
n log n
today
2032
time since “Big Bang”
log-log scale
Solving the 5x5 smileys problem either takes a few seconds, or more time than the universe has been in existence. But, no one knows which for sure!
21 March 2003 CS 200 Spring 2003 12
Who cares about Smiley puzzles?If we had a fast (polynomial time) procedure to solve the smiley puzzle, we would also have a fast procedure to solve the 3/stone/apple/tower puzzle:
3
21 March 2003 CS 200 Spring 2003 13
3SAT Smiley
Step 1: Transform into smileys
Step 2: Solve (using our fast smiley puzzle solving procedure)
Step 3: Invert transform (back into 3SAT problem
21 March 2003 CS 200 Spring 2003 14
The Real 3SAT Problem(also can be quickly transformed
into the Smileys Puzzle)
21 March 2003 CS 200 Spring 2003 15
Propositional GrammarSentence ::= Clause
Sentence Rule: Evaluates to value of Clause
Clause ::= Clause1 Clause2
Or Rule: Evaluates to true if either clause is true
Clause ::= Clause1 Clause2
And Rule: Evaluates to true iff both clauses are true
21 March 2003 CS 200 Spring 2003 16
Propositional GrammarClause ::= Clause
Not Rule: Evaluates to the opposite value of clause (true false)
Clause ::= ( Clause )Group Rule: Evaluates to value of clause.
Clause ::= NameName Rule: Evaluates to value associated with Name.
21 March 2003 CS 200 Spring 2003 17
PropositionExample
Sentence ::= Clause
Clause ::= Clause1 Clause2 (or)
Clause ::= Clause1 Clause2 (and)
Clause ::= Clause (not)
Clause ::= ( Clause )
Clause ::= Name
a (b c) b c
21 March 2003 CS 200 Spring 2003 18
The Satisfiability Problem (SAT)
• Input: a sentence in propositional grammar
• Output: Either a mapping from names to values that satisfies the input sentence or no way (meaning there is no possible assignment that satisfies the input sentence)
21 March 2003 CS 200 Spring 2003 19
SAT Example
SAT (a (b c) b c) { a: true, b: false, c: true } { a: true, b: true, c: false }
SAT (a a) no way
Sentence ::= Clause
Clause ::= Clause1 Clause2 (or)
Clause ::= Clause1 Clause2 (and)
Clause ::= Clause (not)
Clause ::= ( Clause )
Clause ::= Name
21 March 2003 CS 200 Spring 2003 20
The 3SAT Problem• Input: a sentence in propositional
grammar, where each clause is a disjunction of 3 names which may be negated.
• Output: Either a mapping from names to values that satisfies the input sentence or no way (meaning there is no possible assignment that satisfies the input sentence)
21 March 2003 CS 200 Spring 2003 21
3SAT / SAT
Is 3SAT easier or harder than SAT?
It is definitely not harder than SAT, since all 3SAT problemsare also SAT problems. Some SAT problems are not 3SAT problems.
21 March 2003 CS 200 Spring 2003 22
3SAT Example
3SAT ( (a b c) (a b d)
(a b d) (b c d ) ) { a: true, b: false, c: false, d: false}
Sentence ::= Clause
Clause ::= Clause1 Clause2 (or)
Clause ::= Clause1 Clause2 (and)
Clause ::= Clause (not)
Clause ::= ( Clause )
Clause ::= Name
21 March 2003 CS 200 Spring 2003 23
3SAT Smiley• Like 3/stone/apple/tower puzzle, we
can convert every 3SAT problem into a Smiley Puzzle problem!
• Transformation is more complicated, but still polynomial time.
• So, if we have a fast (P) solution to Smiley Puzzle, we have a fast solution to 3SAT also!
21 March 2003 CS 200 Spring 2003 24
NP Complete• Cook and Levin proved that 3SAT was NP-
Complete (1971)• A problem is NP-complete if it is as hard as
the hardest problem in NP• If 3SAT can be transformed into a different
problem in polynomial time, than that problem must also be NP-complete.
• Either all NP-complete problems are tractable (in P) or none of them are!
21 March 2003 CS 200 Spring 2003 25
NP-Complete Problems• Easy way to solve by trying all possible guesses• If given the “yes” answer, quick (in P) way to check
if it is right– Solution to puzzle (see if it looks right)– Assignments of values to names (evaluate logical
proposition in linear time)
• If given the “no” answer, no quick way to check if it is right– No solution (can’t tell there isn’t one)– No way (can’t tell there isn’t one)
21 March 2003 CS 200 Spring 2003 26
Traveling Salesman Problem– Input: a graph of cities and roads with
distance connecting them and a minimum total distant
– Output: either a path that visits each with a cost less than the minimum, or “no”.
• If given a path, easy to check if it visits every city with less than minimum distance traveled
21 March 2003 CS 200 Spring 2003 27
Graph Coloring Problem– Input: a graph of nodes with edges
connecting them and a minimum number of colors
– Output: either a coloring of the nodes such that no connected nodes have the same color, or “no”.
If given a coloring, easy to check if it no connected nodes have the same color, and the number of colors used.
21 March 2003 CS 200 Spring 2003 28
Phylogeny Problem
– Input: a set of n species and their genomes
– Output: a tree that connects all the species in a way that requires the less than k total mutations or “impossible” if there is no such tree.
21 March 2003 CS 200 Spring 2003 29
Minesweeper Consistency Problem– Input: a position of n
squares in the game
Minesweeper– Output: either a
assignment of bombs to
squares, or “no”.
• If given a bomb assignment, easy to check if it is consistent.
21 March 2003 CS 200 Spring 2003 30
Perfect Photomosaic Problem– Input: a set of tiles, a master
image, a color difference function, and a minimum total difference
– Output: either a tiling with total color difference less than the minimum or “no”.
If given a tiling, easy to check if the total color difference is less than the minimum.
Note: not a perfect photomosaic!
21 March 2003 CS 200 Spring 2003 31
Drug Discovery Problem– Input: a set of proteins, a
desired 3D shape– Output: a sequence of
proteins that produces the shape (or impossible)
Note: US Drug sales = $200B/year
If given a sequence, easy (not really) to check if sequence has the right shape.
Caffeine
21 March 2003 CS 200 Spring 2003 32
Is it ever useful to be confident that a problem is
hard?
21 March 2003 CS 200 Spring 2003 33
Factoring Problem– Input: an n-digit number
– Output: two prime factors whose product is the input number
• Easy to multiply to check factors are correct
• Not proven to be NP-Complete (but probably is)
• Most used public key cryptosystem (RSA) depends on this being hard
• See “Sneakers” for what solving this means
21 March 2003 CS 200 Spring 2003 34
NP-Complete Problems• These problems sound really different…but they are
really the same!• A P solution to any NP-Complete problem makes all
of them in P (worth ~$1Trillion)– Solving the minesweeper constraint problem is actually as
good as solving drug discovery!
• A proof that any one of them has no polynomial time solution means none of them have polynomial time solutions (worth ~$1M)
• Most computer scientists think they are intractable…but no one knows for sure!
21 March 2003 CS 200 Spring 2003 35
Speculations• Must study math for 15 years before understanding
an open problem– Was ~10 until Andrew Wiles proved Fermat’s Last
Theorem
• Must study physics for ~6 years before understanding an open problem
• Must study computer science for ~6 weeks before understanding the most important open problem– Unless you’re a 6-year old at Cracker Barrel
• But, every 5 year-old understands the most important open problems in biology!
21 March 2003 CS 200 Spring 2003 36
Charge
• Problem Set 6: Due Monday
• Minesweeper is NP complete (optional)
• We still aren’t sure if the Cracker Barrel Puzzle is NP-Complete– Chris Frost and Mike Peck are working on it
(except Chris is off in Beverly Hills, see Daily Progress article)
– Will present about their proof at a later lecture