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1 CSCI 3 1 1 0 : Assignment 1 ( 6 % of final mark ) posted: May 1 3 th , 2 0 2

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CSCI 3110: Assignment 1(6% of final mark) posted: May 13th,2024
Instructor: Travis Gagie due: 23:59 May 19th,2024
You are allowed to work in groups of up to 3. One person in the group is to submit your answers and
a list of all the group members, and each other person in the group is also to submit a list of all the
group members. You can talk with other groups about the normal assignments but, for everything
you write, someone in your group must be able to explain it. If we ask you to explain what youve
written and no one in your group understands it, then its an academic-integrity offence.
This assignment is due Sunday night at 23:59, Halifax time. There are no SDAs for this course.
Late submissions will not be accepted unless you have an accommodation through the Accessibility
Center that allows you to submit work up to 3 days late, in which case we will accept your
assignment until 23:59 on Wednesday.
1. Give a diagonalization showing that it is impossible to approximate the Kolmogorov Com-
plexity to within a factor of 2.(Hint: Modify the diagonalization in the lecture notes.)
2. Write a propositional-logic formula F on the 12 variables Vr, Vg, Vy, Ir, Ig, Iy, Rr, Rg, Ry, Cr, Cg, Cy
such that there is a bijection between the satisfying truth assignments for F and the valid
3-colourings with the colours red, green and yellow of the 4 counties of Cape Breton Island.
Sketch that bijection.
3. Show that Binary Integer Linear Programming (BILP) is NP-complete by
showing that you can check an alleged solution in polynomial time,
giving a polynomial-time reduction from Independent Set to BILP.
Given a graph G, your reduction should return a BILP instance whose objective function has
value at least k if and only if G has an independent set of size at least k.
4. Apply your reduction to the graph in Figure 2.3 in the lecture notes. (If you just write any
old BILP instance whose objective function has value at least 4 because you can see there is
an independent set of 4 vertices, then you wont have applied a reduction and youll get 0.)
5. Suppose you want to prove to your friend have a solution to an instance of an NP-complete
problem X, but you dont want to tell them the solution. How can you use the zero-knowledge
proof of knowledge for 3-Col to do this? (Hint: Use the fact that 3-Col is NP-complete.)
6. Give an algorithm that, given a connected graph G on n vertices with n +5 edges for some
constant c, finds a minimum-size vertex cover for G in O(n) time. (Hint: Use BFS or DFS to
select a subgraph of G thats a tree on n vertices and consider the 6 leftover edges that arent
in that tree; consider how you could cover those 6 edges for each, take one end, take other
or take both and think about what to do for each of the at most 36=729 possibilities.)
Bonus: To show a problem X is NP-complete, 1) we show X can be solved on an NP Turing machine
and 2) we reduce a know NP-complete problem to X (thus showing we can program an
NP Turing machine in X). When we show a programming language Y is Turing-complete,
however, we just show we can program a Turing machine in Y ; why dont we show that Y
can be interpreted on a Turing machine?

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