IT-Universitetet i København
  Tilbage Kursusoversigt
Kursusnavn (dansk):Intelligent Systems Programming (tidligere Effektiv AI) 
Kursusnavn (engelsk):Intelligent Systems Programming (formerly Efficient AI)  
Semester:Forår 2012 
Udbydes, softwareudvikling og -teknologi (sdt) 
Omfang i ECTS:7,50 
Min. antal deltagere:12 
Forventet antal deltagere:60 
Maks. antal deltagere:130 
Formelle forudsætninger:You must have passed an elementary programming course.

Many students, however, find this an insufficient requirement. We are working on a solution to this. In the mean time it is strongly recommended that you have passed an algorithms class or take it in parallel with this course. It is also strongly recommended that you have passed a discrete math course or take it in parallel with this course.

Notice that this course is NOT a formal requirement for MTG students.

If you are an external student, it is important that you have programming-experience from elsewhere, i.e. through a daily use in a developer position in the software industry.

Information about the course of study
This course is part of a specialization on the Master of Science in IT, study programme Software Development and Technology. See a description of specializations on SDT here:
Kandidat Software Development Technology

Information about the course of study
This course is second part of a specialization on the Master of Science in IT, study programme Media Technology and Games. See a description of specializations on MTG here: Master of Science Media Technology and Games 
Læringsmål:After the course, the student should be able to:
* Identify decision problems in work processes and IT products that can
be solved by AI and optimization algorithms.
* Apply advanced AI and optimization modeling techniques to describe
these problems formally.
* Implement AI and optimization software components to solve
these problems efficiently.
* Apply standard AI and optimization models and solvers.
* Participate in concept development of advanced decision
support systems. 
Fagligt indhold:The overall goal of the course is to introduce students to a selection of the most important problem solving and decision support techniques within AI and optimization. The goal is to make students able to identify, design, and implement efficient solutions to the kind of decision problems that arise in modern organizations and IT products. The expectation is that a student mastering the material is able to work in internationally leveled business intelligence and optimization groups as well as in development departments of “intelligent” applications as used in smart phones, computer games, enterprise resource planning systems, and decisions support systems.

The course will cover the followings topics:

Search algorithms
* Informed search: greedy heuristic search, A*, breadth-first heuristic search
* Local search: hill-climbing, simulated annealing, genetic algorithms, tabu search, population-based search
* Adversarial search: Minimax search, alpha-beta pruning

Propositional logic
* Representations: disjunctive (DNF), conjunctive (CNF), and if-then-else (INF) normal forms, Binary Decision Diagrams (BDDs)
* Reasoning: resolution, SAT-checking

Constraint programming
* Local consistency: arc-consistency, path-consistency, i-consistency
* Look-ahead search strategies: forward-checking, arc-consistency look-ahead, maintaining arc-consistency

Linear Programming
* Simplex algorithm
* Duality

The course provides useful tools in its own right, but it is also the first course on the modern AI specialization and the scalable computing specialization. 
Læringsaktiviteter:14 ugers undervisning bestående af forelæsninger og øvelser

13 lectures + 11 exercise sessions.

Some mandatory homework.

See the schedule here:
link to the time table
The schedule will be available shortly before the beginning of the term. 

Eksamensform og -beskrivelse:X. experimental examination form (7-scale; external exam), 7-trins-skala, Ekstern censur

This course has mandatory assignments (e.g. attendance, papers, exercises, presentations, productions), that need to be completed/approved before being eligible to register for the examination:
- Mandatory homework  

Litteratur udover forskningsartikler:1) Russel, S and Norvig, P., "Artificial Intelligence: A Modern Approach", Third Edition, Prentice Hall, 2010, ISBN-13 978-0132071482

2) Notes 
Afholdelse (tid og sted)
Kurset afholdes på følgende tid og sted:
Torsdag 08.00-09.50 Forelæsning ITU Aud 2
Torsdag 10.00-11.50 Øvelser ITU Aud 2

Eksamen afholdes på følgende tid og sted:
2012-06-04 9-13 Skriftlig eksamen ITU 4A14/16 + 2A12/14