Problem Solving and Search in Artificial
Intelligence
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Course Syllabus
Course Number: 181.190 - Lecture with Exercises (SS 2013) Course
Title: Problem Solving and Search in
Artificial Intelligence Credits: 2,0 Std.
(3ECTS-Points) Lecturer: Priv. Doz. Dr. Nysret Musliu Email: musliu@dbai.tuwien.ac.at |
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Course
Description: This course
teaches the main artificial intelligence search techniques used for problem
solving. The emphasis will be in informed search techniques, constraint
satisfaction, advanced heuristic search techniques, and application of
machine learning in search. The course covers these topics: · Basic Concepts · Uninformed Search Strategies · Heuristic Algorithms · Constraint Satisfaction Problems · Constraint Programming Techniques ·
Decomposition Techniques (Tree and Hypertree Decompositions) ·
Metaheuristic Algorithms (Simulated Annealing, Tabu Search, Genetic
Algorithms…) ·
Adversarial Search and Game Playing ·
Application of Machine Learning in Search
(Automated Algorithm Selection, Hyperheuristics) ·
Algorithm Configuration (Automated Parameter Tuning) The use of
search methods will be illustrated by examples, which show the application of
these methods for solving of different hard problems with high practical
relevance. Moreover, successful use of search methods in research and
industrial projects of our group will be presented. Course
Structure: This course
is combination of lectures and exercises. Exercises part consists on small
project, which will be an implementation of a hybrid method that combines
metaheuristic algorithms and constraint programming technique for a
particular problem. Additionally, during the course discussion for solving of
different logical problems and puzzles will be made. Proposals of students
for discussions about problems for which they are interested are
encouraged. Literature: Stuart
Russell and Peter Norvig . Artificial Intelligence: A Modern Approach (Third
Edition), 2010 Z.
Michalewicz and D. B. Fogel. How to Solve It: Modern Heuristics, 2nd edition,
Springer-Verlag, 2004 Additionally
the key papers from the literature will be used. … Grading Final
(written) Exam: 60 points Project: 40
points For a positive grade you must have at least 50
points and in the final exam you must reach at least 30 points Schedule of
Classes Lectures 07.03.2013 (10:00 - 12:00) (Seminarraum
Gödel) Preliminary
discussion Basic Concepts (How to Solve It: Modern Heuristics -
Chapters 1, 2 ; Artificial Intelligence: A Modern Approach
(AIMA) - Chapter 3) 14.03.2013 (10:00 - 12:00) (Seminarraum
Gödel) Uninformed Search Strategies (AIMA - Chapter
3, How to Solve It - Chapters 3) Informed
Search Algorithms (AIMA - Chapter
4, How to Solve It: Modern Heuristics - Chapters 4) 21.03.2013 (10:00 - 12:00) (Seminarraum
Gödel) Constraint Satisfaction (AIMA - Chapter 5) 11.04.2013 (10:00 - 12:00) (Seminarraum
Gödel) Constraint
Programming Techniques (AIMA - Chapter 5) 18.04.2013 (10:00 - 12:00) (Seminarraum
Gödel) Structural Decomposition
Techniques (Tree/Hypertree Decompositions) 25.04.2013 (10:00 - 12:00) (Seminarraum
Gödel) Metaheuristic
Algorithms 16.05.2013 (10:00 - 12:00) (Seminarraum
Gödel) Metaheuristic
Algorithms 23.05.2013 (10:00 - 12:00) (Seminarraum
Gödel) Application of Machine Learning in Search (Automated
Algorithm Selection, Hyperheuristics) 06.06.2013 (10:00 - 12:00) (Seminarraum
Gödel) Algorithm
Configuration (Automated Parameter Tuning) Adversarial
Search and Game Playing 20.06.2013 (10:00 – 12:00) (Seminarraum
Gödel) Presentation
of projects 27.06.2013 (10:00 – 12:00) (Seminarraum Gödel) Final Exam Project You will implement methods that will be considered
in this class for the Sudoku problem. More information for this problem can be found in
this paper: Jean-Paul Delahaye. The
Science behind Sudoku. Scientific American, May 22, 2006 Additional information for existing constraint
programming techniques and metehuristic algorithms for this problem will be
given during the class. The project consists of two phases. Phase I:
Implementation of a constraint programming technique for Sudoku Phase II:
Implementation of a metaheuristic technique (or hybrid technique) for Sudoku 2 students can work together in a group Schedule for the
Assignment: 05.05.2013: Submit in TUWEL your implementation (source code and
the description of your method) for Phase I 10.06.2013 Submit in TUWEL your implementation (source code and
the description of your method) for Phase II 20.06.2013 (10:00 – 12:00) (Seminarraum
Gödel) Presentation
of projects |
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mailto: musliu@dbai.tuwien.ac.at |