Attention:

• Email address for questions: eki-2016s AT kr.tuwien.ac.at
• Course start: Tue Mar 1 2016. Course dates are provisional.
• Mandatory TISS course and group registration until Mar 4, 2016. Belated registration will be ignored.
• Mandatory TUWEL entry test on Mon Mar 7 and Tue Mar 8 (test available 00:00-23:55)

Overview of concepts, methods, and applications in Artificial Intelligence.

Didactic Procedure

• Lecture and Exercises
• Processing of exercises by students
• Short oral presentation and discussion of solutions and results

The following subjects will be discussed:

• historical and philosophical aspects of AI
• search
• constraint satisfaction problems
• planning
• decision theory

Lecturers

• Lecture part: Thomas Eiter and Hans Tompits
• Exercise part: Thomas Eiter, Hans Tompits, and Christoph Redl

Course of Action and Topics of the Lecture Part

• Tue Mar 01: Organisation, What is AI? (Eiter)
• Tue Mar 08: Intelligent agents, Problem solving and search (Eiter)
• Tue Mar 15: Informed search algorithms, Local search (Eiter)
• Tue Mar 22: Easter break
• Tue Mar 29: Easter break
• Tue Apr 05: Learning from observations (Eiter)
• Tue Apr 12: Learning from observations, ctd (Eiter)
• Tue Apr 19: Neural networks (Eiter)
• Tue Apr 26: Constraint satisfaction problems (Tompits)
• Tue May 03: Planning I (Tompits)
  
• Tue May 10: Planning II (Tompits)
• Tue May 17: Pentecost break
• Tue May 24: Decision theory I (Tompits)
• Tue May 31: Decision theory II (Tompits)
• Tue Jun 07: Philosophical foundations of AI (Tompits)

Exercise Part

Mandatory registration until Mar 4.

Entry test

The mandatory TUWEL entry test will be available only on Mon Mar 07 and Tue Mar 08 (00:00-23:55, three submissions possible, last submission counts).

Checkmark lists and solution discussion

• Mode: Checkmark lists in TUWEL and a solution discussion of 1 hour in groups of 3 students (students must be able to present and explain their solutions and background); details and dates are announced via TUWEL
• Evaluation: exercise discussions are evaluated with 0-15 points; this is weighted with the percentage of checked examples and rounded to the next integer.

3 exercise sheets

• Sheet 1: Search
• Sheet 2: Learning and Neural Networks
• Sheet 3: CSP, Planning, and Making Simple Decisions

ECTS breakdown: 3 ECTS = 75 hours

• Lectures, course introduction 24h
• Entry test 0.5h
• Solving the exercises 20h
• Presenting the exercises 1h
• Preparation for the final exam 28h
• Final exam 1.5h

Exercise part

• The entry test is totalling 5 pts.
• The 3 exercise sheets with the according discusion are totalling 15 pts.
• Total pts: 20

Lecture part

• Written closed book exam
• Total pts: 80

Total sum of points for lecture and exercise part: 100

Zero tolerance for unfair practice (e.g., plagiarism, copied solutions, ...). All involved persons will be fined with 0 pts. (You may get a negative certificate).

Grading

Requirements for a positive certificate:

• at least 3 points for the entry test; and
• at least 40 points for the written final exam; and
• at least 51 points in total.

The course will be graded as follows:

• < 51 pts: N5 (Nicht Genügend)
• >= 51 pts: G4 (Genügend)
• >= 63 pts: B3 (Befriedigend)
• >= 75 pts: U2 (Gut)
• >= 88 pts: S1 (Sehr Gut)

Please register first for the course.

• Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd edition. Prentice Hall, 2010 (http://aima.cs.berkeley.edu/)
• Stuart Russell, Peter Norvig: Künstliche Intelligenz: Ein moderner Ansatz. 3., überarbeitete Auflage, Pearson Deutschland, 2012.
• ...