Artificial Intelligence II

  • "Intelligence: The ability to learn and solve problems" [Webster's dictionary]
  • "Artificial Intelligence is the intelligence exhibited by machines or software" [Wikipedia]
  • "The science and engineering of making intelligent machines" [McCarthy]
  • "The study and design of intelligent agents, where an intelligent agent is a system that perceived its environment and takes actions that maximize its chances of success" [Russel and Norvig AI book]

LECTURER

Prof. Dr. techn. Wolfgang Nejdl
Professorinnen und Professoren

COURSE CONTENT

  • Probability
  • Bayes' Nets: Representation, Independence, Inference and sampling
  • Decision networks
  • Hidden Markov Models, Particle Filters and Applications
  • Machine learning:
    • Naive Bayes
    • Perceptions and Logistic Regression
    • Optimization and Neural Networks
    • Decision trees
  • Robotics / Language / Vision

TEACHING ASSISTANTS

SCHEDULE AND OTHER INFORMATION

Lecture: Mondays 13:00 - 14:30 (start : 21 Oct 2019)

Tutorials: Mondays: 12:15 - 13:00 and Fridays: 16:15 - 17:00 (start : 1 Nov 2019)

Room: Multimedia Auditorium 023, building 3703, Appelstrasse 4 (lectures and tutorials

ECTS : 5

LITERATURE

Artificial Intelligence: A Modern Approach (3rd Edition) by Stuart Russell and Peter Norvig.

The lecture notes and exercises are based on the following course:

EXAM

  • The exam will take place on 11 February  2020  at 15:30.
  • The exam duration is 90 minutes.
  • The only allowed aid is a one-sided sheet of paper with handwritten notes.

Exercises

28/10/2019:    Exercise1     solution

04/11/2019:    Exercise2     solution

18/11/2019:    Exercise3     solution

25/11/2019:    Exercise4     solution

02/12/2019:    Exercise5     solution

09/12/2019:    Exercise6     solution

16/12/2019:    Exercise7     solution

06/01/2020:    Exercise8     solution

13/01/2020:    Exercise9     solution

01/20/2020:    Exercise10   solution

01/27/2020:    Exercise11    solution

Projects

09/12/2019: Project 1: Ghostbusters - code
Submission due: 10/01/2020

20/01/2020: Project 2: Machine Learning - code
Submission due: 07/02/2020