IT-Universitetet i København
 
  Tilbage Kursusoversigt
Kursusbeskrivelse
Kursusnavn (dansk):Intelligent Systems Programming (formerly Efficient AI) 
Kursusnavn (engelsk):Intelligent Systems Programming (formerly Efficient AI) 
Semester:Forår 2013 
Udbydes under:cand.it., softwareudvikling og -teknologi (sdt) 
Omfang i ECTS:7,50 
Kursussprog:Engelsk 
Kursushjemmeside:http://www.decisionoptimizationlab.dk/index.php/teaching/msc-courses/2-uncategorised/58-intelligent-systems-programming-2013 
Min. antal deltagere:12 
Forventet antal deltagere:60 
Maks. antal deltagere:130 
Formelle forudsætninger:*You must have passed an elementary programming course. (for example
Introductory Programming)
*You must have passed a discrete mathematics course (for example Foundations of Computing, Discrete Mathematics)
*You must follow in parallel, or have passed an introductory algorithms course (for example Foundations of Computing, Algorithms and Data Structures).

Notice that these courses are NOT a formal requirement for GAMES 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.

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.
This course is first part of a specialization on the Master of Science in IT, study programme 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. 

Obligatoriske aktivititer:Mandatory Exercises. Exercises marked "*Exercises" have a mandatory problem. You must hand-in and pass 3 of these to qualify for taking the exam.

Mandatory projects. During the semester there will be 3 implementation projects. You must hand-in and pass 2 of these to qualify for taking the exam. 
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:
UgedagTidspunktForelæsning/ØvelserStedLokale
Torsdag 10.00-11.50 Forelæsning ITU Aud 2
Torsdag 12.00-13.50 Øvelser ITU 2A12, 2A14

Eksamen afholdes på følgende tid og sted:
EksamensdatoTidspunktEksamenstypeStedLokale
2013-06-06 09-13 Skriftlig eksamen ITU 2A12/2A14, 4A16