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21cs422 [2021-07-30] – created Martin Ziegler21cs422 [2021-11-30] (current) – [Synopsis/Syllabus:] Martin Ziegler
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 We make a special pedagogical effort to avoid the arduous Turing machine formalism and instead employ a variant of WHILE programs. We make a special pedagogical effort to avoid the arduous Turing machine formalism and instead employ a variant of WHILE programs.
  
-IMotivating Examples ({{cs422a.ppt|ppt}}, {{cs422a.pdf|pdf}}): +0Motivation 
-  * comparison-based sorting +
-  * finite automata +
-  * asymptotic cost +
-  * addition chain +
-  * matrix multiplication +
-  * diagonalization / undecidable Halting Problem+
  
-II. Basic Computability Theory ({{cs422b.ppt|ppt}}, {{cs422b.pdf|pdf}}):+I. Basic Computability Theory ({{cs422a.ppt|ppt}}, {{cs422a.pdf|pdf}}):
   * Un-/Semi-Decidability and Enumerability   * Un-/Semi-Decidability and Enumerability
   * Reduction, degrees of undecidabiliy   * Reduction, degrees of undecidabiliy
-  * Busy Beaver/Rado function+  * (Post's Correspondence Problem, truth of arithmetic formulae) 
 +  * Busy Beaver function 
 +  * Ackermann's Function
   * LOOP programs   * LOOP programs
   * and their capabilities    * and their capabilities 
-  * Ackermann's Function 
  
-III. Advanced Computability ({{cs422c.ppt|ppt}}, {{cs422c.pdf|pdf}}):+II. Advanced Computability ({{cs422b.ppt|ppt}}, {{cs422b.pdf|pdf}}):
   * WHILE programs   * WHILE programs
   * UTM Theorem   * UTM Theorem
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   * SMN Theorem / Currying (Schönfinkeling)   * SMN Theorem / Currying (Schönfinkeling)
   * Recursion Theorem, Fixedpoint Theorem, QUINES   * Recursion Theorem, Fixedpoint Theorem, QUINES
-  * Oracle WHILE Programs, Post/Friedberg/Muchnik +  * Oracle WHILE Programs
   * Arithmetic Hierarchy   * Arithmetic Hierarchy
-  * (Post's Correspondence Problem, truth of arithmetic formulae)+  * Post/Friedberg/Muchnik 
  
-IV. Computational Complexity ({{cs422d.ppt|ppt}}, {{cs422d.pdf|pdf}}):+III. Computational Complexity ({{cs422c.ppt|ppt}}, {{cs422c.pdf|pdf}}):
   * Model of computation with (bit) cost: WHILE+   * Model of computation with (bit) cost: WHILE+
   * Complexity classes P, NP, PSPACE, EXP   * Complexity classes P, NP, PSPACE, EXP
   * and their inclusion relations   * and their inclusion relations
 +  * Example problems: Euler/Hamiltonian Circuit, Edge/Vertex Cover
 +  * Boolean formulas and Satisfiability
   * nondeterministic WHILE+ programs   * nondeterministic WHILE+ programs
-  * Example problemsEuler Circuit, Edge Cover +  * Time Hierarchy TheoremP≠EXP
-  * Example problems: Hamiltonian Circuit, Vertex Cover, Independent Set, Clique, Boolean Satisfiability, Integer Linear Programming +
-  * Boolean formulas +
  
-V. Structural Complexity / NPc ({{cs422e.ppt|ppt}}, {{cs422e.pdf|pdf}}): +IV. Structural Complexity / NPc ({{cs422d.ppt|ppt}}, {{cs422d.pdf|pdf}}): 
-  * polynomial-time reductions +  * polynomial-time reduction 
-  * equivalent problems CliqueIndependent SetBoolean Satisfiability3-Satisfiability+  * equivalent problemsClique Independent Set <= Boolean Satisfiability <= 3-Satisfiability <= Independent Set
   * Cook-Levin Theorem, Master Reduction   * Cook-Levin Theorem, Master Reduction
-  * Ladner's Theorem (without proof)+  * Bin Packing is NP-complete 
 +  * Scenarios for P/NP, Ladner's Theorem 
  
-VI. PSPACE and Polynomial Hierarchy ({{cs422f.ppt|ppt}}, {{cs422f.pdf|pdf}}): +V. PSPACE and Polynomial Hierarchy ({{cs422e.ppt|ppt}}, {{cs422e.pdf|pdf}}): 
-  * PSPACE-completeness +  * PSPACE and QBF 
-  * QBF, 3QBF, GRAPH +  * Master Reduction 
-  * Savitch's Theorem +  * A PSPACE-complete Two-Player Game on Digraphs 
-  * Oracle Computation +  * Savitch's Theorem: NSPACE(f) in SPACE(f²) 
-  * Quantifier Alternations+  * Immerman-Szelepcsényi: NSPACE(f) = coNSPACE(f) 
 +  * Oracle Complexity and Polynomial Hierarchy, Semantically and Syntactically 
 +  * Limitations of Relativizing Proofs: Baker, Gill & Solovay;  Bennett & Gill 
  
-VIIAdvanced Complexity  ({{cs422g.ppt|ppt}}, {{cs422g.pdf|pdf}}): +VIPerspectives ({{cs422f.ppt|ppt}}, {{cs422f.pdf|pdf}}):
-  * (Time Hierarchy)+
   * complexity of cryptography: UP and one-way functions   * complexity of cryptography: UP and one-way functions
-  * (counting problemsToda's Theorem) +  * counting problems: #P and Toda's Theorem 
-  * (LOGSPACE, Immerman-Szelepcsenyi Theorem) +  * Approximation algorithms and hardness 
-  * (Approximation algorithms and hardness) +  * randomized algorithms, probability amplification, BPP, Adleman and Sipser-Gacs-Lautemann Theorems 
-  * (randomized algorithms, probability amplification, BPP, Adleman and Sipser-Gacs-Lautemann Theorems)+  * fixed-parameter tractability and hardness
  
 ===== Homework/Assignments =====  ===== Homework/Assignments ===== 
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 ===== E-Learning =====  ===== E-Learning ===== 
- * [[http://klms.kaist.ac.kr |KLMS]]  +   * [[https://www.youtube.com/playlist?list=PLvcvykdwsGNG3TUu_dPMLdXMjVxLKpbzf|YouTube]] 
 +   * [[https://klms.kaist.ac.kr/course/view.php?id=130178|KLMS]]  
 +   * Due to the large number (>80) of students enrolled, we unfortunately cannot answer questions by email. \\ 
 +Instead please use the KLMS Bulletin Board or visit the TAs during their office hours.