Course summary
| Credits | 5 cr |
| Level of the Course | The course is only for students who have completed their general studies. |
| Teaching Period | III - IV (Spring) |
| Workload | Lectures: 20 Teaching in small groups: 20 Examinations: 3 Programming assignments: 30 Other independent work (including preparing for the examination): 60 |
| Learning Outcomes | At this course you will learn to represent combinatorial search problems in terms of propositional satisfiability, constraint programming, and integer programming formulations. You will obtain a basic understanding of linear programming methodology and become familiar with several types of local search techniques. Having completed the course, you will be able to translate your problem into an appropriate general formulation and use a generic problem solver to solve the problem, or design a local search method tailored specifically to your problem of interest. |
| Content | Search spaces and search methods. Backtracking, local and heuristic search. Representing and solving search problems using propositional satisfiability, constraint programming, and integer programming techniques. |
| Assessment Methods and Criteria | Examination and three programming assignments. The course grade is
determined by points earned from the exam, programming assignments, and tutorials (see the first lecture for details). |
| Study Material | Lecture slides and tutorial materials. |
| Substitutes for Courses | Replaces former course T-79.3001 (Logic in Computer Science: Foundations) and T-79.4101 (Discrete Models and Search). |
| Prerequisites | Boolean logic, linear algebra, and basic programming skills |
| Grading Scale | 0-5 |
| Registration for the Course | In Oodi. |
| Language of Instruction | EN. English. |
| Course Staff and Contact Information |
Lecturers: Shahab Tasharrofi
Tutorials: Jori Bomanson |
| Office Hours | Wednesdays 3 PM - 4 PM (C311). Otherwise by appointment. |