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====== Laborator AA ====== | ====== Laborator AA ====== | ||
- | ==== Masina Turing ==== | + | ===== Part 1 - Decidability - 4 labs ===== |
+ | |||
+ | ==== 1. Turing Machine ==== | ||
Key concepts: | Key concepts: | ||
Line 48: | Line 50: | ||
- | ==== Turing Machines and Solvability ==== | + | ==== 2. Turing Machines and Solvability ==== |
+ | Key concepts: | ||
+ | * **acceptance** vs **decision** | ||
+ | * complement of a problem. | ||
+ | * Can the following problem be **accepted** by a TM? (f(x) = 0) | ||
+ | * What is the complement of this problem? | ||
+ | * Can a problem be accepted by two different TMs? Can a TM accept two different problems? | ||
+ | * If a problem is accepted by some TM, can its complement also be accepted? | ||
+ | * If a problem is **decided** by some TM, can its complement also be decided? | ||
+ | * Write a TM which accepts //is-odd// problem but which does not decide it. | ||
+ | * Which of the following problems you **think** can be **accepted** and which can be **decided**? Use pseudocode instead of writing a TM. | ||
+ | * a) V [[https://arxiv.org/pdf/1902.10188.pdf | Undecidable example 1]] | ||
+ | * b) V [[https://en.wikipedia.org/wiki/Hilbert%27s_tenth_problem | Hilbert undecidable ]] | ||
+ | * c) V [[https://en.wikipedia.org/wiki/Wang_tile | Wang Tile]] | ||
+ | * e) k-color | ||
+ | * f) Linear Integer Programming | ||
+ | ==== 3. The Universal Turing Machine ==== | ||
+ | Key concepts: | ||
+ | * simulation | ||
+ | Exercises: | ||
+ | * The Von Newmann architecture - explained. | ||
+ | * Which of the components of Von Newmann arch. corresponds best to the TM? | ||
+ | * Write a TM pseudocode which verifies if a word is the proper encoding of a TM. | ||
+ | Discussion on the pseudocode. | ||
+ | * Write a TM pseudocode which accepts if **there exists** a word which is accepted by a given TM in **k steps**. | ||
+ | Discussion on the pseudocode | ||
+ | * Which of the following is a suitable pseudocode for a TM: | ||
+ | <code> | ||
+ | Algoritm(M,w){ | ||
+ | if size(w) > 10 | ||
+ | then if M halts for w in k steps | ||
+ | accept. | ||
+ | } | ||
+ | </code> | ||
+ | <code> | ||
+ | Algoritm(M1,M2,w){ | ||
+ | k = 0 | ||
+ | while true | ||
+ | if M1(w) has the same behaviour as M2(w) after k steps | ||
+ | then accept | ||
+ | else k = k + 1 | ||
+ | } | ||
+ | </code> | ||
+ | <code> | ||
+ | Algorithm(M,A) { | ||
+ | // A is a finite set of words | ||
+ | for each w in A | ||
+ | if M(w) halts //undecidable! Pseudocode is ok, but this machine may not terminate | ||
+ | then accept | ||
+ | } | ||
+ | </code> | ||
+ | <code> | ||
+ | Algorithm(M,w) { | ||
+ | build the machine M' such that M(x) accepts iff M'(x) does not accept, for all words x | ||
+ | if M'(w) in 1000 steps | ||
+ | accept | ||
+ | } | ||
+ | </code> | ||
+ | <code> | ||
+ | Algorithm(M1,M2) { | ||
+ | if M1 always halts then //we know of no procedure, terminating or not, which can achieve this. This is not a proper TM/algorithm. | ||
+ | if M2 always halts then | ||
+ | accept | ||
+ | } | ||
+ | </code> | ||
+ | |||
+ | * Write the problem which is accepted by each of the above machines. | ||
+ | * Write a TM pseudocode which accepts if a **given** word is accepted by two given TMs. Explain the dovetailing technique. | ||
+ | |||
+ | Homework: | ||
+ | * Write a TM pseudocode which accepts if **there exists** a word which is accepted by two given TMs. | ||
+ | * Write a TM pseudocode which accepts if **there exists** a TM which accepts a given word. | ||
+ | * Write a TM pseudocode which accepts if a given TM accepts **some** word of a given finite set A. | ||
+ | * Write a TM pseudocode which accepts if a given TM accepts **all** words of a given finite set A. | ||
- | * Exercitii simple cu MT | ||
- | * Exercitii cu MTU si conceptul de simulare | ||
[[https://www.bbc.co.uk/bitesize/guides/zhppfcw/revision/3#:~:text=Von%20Neumann%20architecture%20is%20the,both%20stored%20in%20primary%20storage | Von Newmann Model]] | [[https://www.bbc.co.uk/bitesize/guides/zhppfcw/revision/3#:~:text=Von%20Neumann%20architecture%20is%20the,both%20stored%20in%20primary%20storage | Von Newmann Model]] | ||
- | * Algoritmi | + | ==== 4. Undecidable problems ==== |
- | ==== Decidabilitate ==== | + | Key concept: |
+ | * reduction | ||
+ | * proving a problem is not in R | ||
+ | * proving a problem is not in RE | ||
+ | |||
+ | ===== Part 2 - Measuring algorithm performance (3 labs) ===== | ||
- | * Ce este o problema de decizie? | ||
- | * Problema si rezolvare; | ||
- | * Lista de probleme care (pot/nu pot) fi rezolvate; | ||
- | * Reduceri | ||
- | * Further work: coRE, complement, dovetailing | ||
==== Notatii asimptotice ==== | ==== Notatii asimptotice ==== | ||
- | * Implementari care sa ilustreze faptul ca constanta conteaza/nuconteaza | + | * (Homework) Implement mergesort and insertionsort in python. Use a large dataset (provided by us) to test your implementation. Plot the execution times together with the functions $math[n^2] and $math[n\cdot \log{n}] using ''gnuplot''. What do you observe? Adjust the constants for the previous functions so that the rate of growth can be better observed. |
- | * Implementari care sa ilustreze faptul ca log n >> n >> n2 >>> n3 | + | |
- | * Grafice (in ?!) | + | |
* Exercitii clasice | * Exercitii clasice | ||
==== Recurente ==== | ==== Recurente ==== | ||
* Cativa algoritmi si recurentele lor | * Cativa algoritmi si recurentele lor | ||
+ | * Merge-sort, | ||
+ | * Quick-sort (curs) | ||
+ | * Exemplul cu sqrt(n) al lui Sebi. | ||
* Exercitii clasice | * Exercitii clasice | ||
+ | |||
+ | ==== Ammortised Analysis ==== | ||
+ | * Classical exercises | ||
+ | |||
+ | ===== Part 3 - Algorithm complexity (4 labs) ===== | ||
==== NP completitudine ==== | ==== NP completitudine ==== | ||
- | * Implementare care sa ilustreze exponentiala (backtracking); legatura cu MTN. | + | * Implement a SAT solver which encodes formulae as matrices and iterates over interpretations treating them as binary counters. Plot execution times. |
- | * Reduceri pentru SAT solvere | + | * Implement a better SAT solver which uses BDDs to encode a formula. The variable ordering is known in advance. Plot execution times. |
- | * Exercitii clasice cu reduceri | + | * Implement a k-Vertex-Cover solver using a reduction from SAT, and any of the above solvers. |
+ | * Exercitii clasice cu choice si reduceri | ||
+ | |||
+ | ===== Part 4 - Abstract Datatypes (2 labs) ===== | ||
==== TDA-uri ==== | ==== TDA-uri ==== | ||
* Conceptul de operator vs cel de functie (exercitiu in C, exercitiu in Haskell, pe Liste) | * Conceptul de operator vs cel de functie (exercitiu in C, exercitiu in Haskell, pe Liste) | ||
+ | * (Homework) Implementare LinkedList si ArrayList in Python, impreuna cu operatii. Implementare Haskell a operatiilor, dupa o discutie la curs despre acestea. | ||
* Exercitii clasice | * Exercitii clasice | ||