Algorithmic Problem Solving Feel the satisfaction of attacking a really hard problem

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Algorithmic Problem Solving Feel the
satisfaction of attacking a really hard problem
and solving it!

• This is a hands-on course on studying, combining,
  and applying diverse algorithmic techniques,
  approaches, and heuristics for solving hard
  computational problems.
• How do computers play chess? How do they prove
  theorems? How do they find optimal routes to
  visit many destinations, schedule commodities
  flows, arrange optimal packings and facilities
  allocations? This course introduces and explains
  various appropriate algorithmic and heuristic
  methods that help to cleverly reduce and explore
  astronomically large search spaces with the
  purpose of finding optimal or near-optimal
  solutions in reasonable time.
• As an example, a familiar local search heuristic
  (hill climbing in the picture) can be refined and
  adjusted to solve hard problems like Traveling
  Salesman, Satisfiability, Graph Coloring,and
  Bin Packing.

• Dynamic programming (known from AD2) helps
  solving chess endgames efficiently and
  exhaustively. Intelligent traversal of a search
  tree cutting away nonproductive branches
  (branch-and-bound, alpha-beta cut) helps to
  outsmart adversaries in games and to solve
  complex problems in artificial intelligence and
  planning.
• Methods of approximating a problem, representing
  it by a linear program, and solving its
  relaxation efficiently allow for solving a wide
  range of practically important problems. Using
  randomization often adds power and efficiency to
  algorithms, allows to avoid worst-case behaviors
  and improves solution quality.
• Each participant suggests, works on, presents,
  defends an individual project, and creates a web
  site, either starting from a method, algorithm or
  heuristic, or from a (presumably) hard
  algorithmic problem. Both variants usually give
  surprising and unexpected results.

Prerequisites Algorithms and data structures
DV2, logic, linear algebra, discrete
mathematics, probability and statistics, advanced
programming. Goal Boosting students'
algorithmic expertise and sophistication, giving
taste and skills for combining advanced tools for
solving hard problems, orienting students in
their (future) research.