Biological and Artificial Intelligent Systems
A.Y. 2019/2020
Learning objectives
The course aims to provide students with the basics of Artificial Intelligence with an interdisciplinary approach to the scientific and philosophical research, supported by practical activities.
Expected learning outcomes
Knowledge and understanding
At the end of the course the student
- knows the fundamental elements of Artificial Intelligence and can understand the frontiers
- knows the fundamental methods and how use software platforms to develop some machine learning algorithms
- understands and can discuss about philosophical and technological issues
Ability to apply knowledge and understanding
- can apply the acquired knowledge to the development of fundamental algorithms
- can discuss about Artificial Intelligence and the related philosophical problems
- can interpret Artificial Intelligence methods by relating them to their processing contexts and their respective functions
- can apply the acquired knowledge to concepts of different interdisciplinary nature.
At the end of the course the student
- knows the fundamental elements of Artificial Intelligence and can understand the frontiers
- knows the fundamental methods and how use software platforms to develop some machine learning algorithms
- understands and can discuss about philosophical and technological issues
Ability to apply knowledge and understanding
- can apply the acquired knowledge to the development of fundamental algorithms
- can discuss about Artificial Intelligence and the related philosophical problems
- can interpret Artificial Intelligence methods by relating them to their processing contexts and their respective functions
- can apply the acquired knowledge to concepts of different interdisciplinary nature.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
Course topic: Intelligent systems, 6 cfu, 40 hours
Teaching unit A (3 CFU, 20 hours): Bases of the AI. Differences between biological and artificial intelligent systems. 3 CFU, 20 hours
B teaching unit (3 CFU, 20 hours): Machine learning. Philosophy, ethics. 3 CFU, 20 hours
Presentation of the course
Introduction to AI (Artificial Intelligence) from the point of view of the differences between biological and artificial intelligent systems. Logic, GOFAI (Good Old Fashion Artificial Intelligence - the old Artificial Intelligence models), strong and weak AI, Turing Test. Machine learning. AI philosophy. Ethical implications.
Examination program for attending and non-attending students
Teaching unit A
· "ARTIFICIAL INTELLIGENCE - Vol.2, a modern approach", 2nd edition, by Peter Norvig and Stuart Russel, published by Pearson
· Lecture notes by the teacher
· Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements
· Teaching unit B
· Lecture notes by the teacher
· Other material communicated from time to time in class
Warning
National and international students or Erasmus incoming are invited to make timely contact with the course professor.
The examination procedures for students with disabilities and/or with DSA must be agreed with the teacher, in agreement with the competent Office.
Teaching unit A (3 CFU, 20 hours): Bases of the AI. Differences between biological and artificial intelligent systems. 3 CFU, 20 hours
B teaching unit (3 CFU, 20 hours): Machine learning. Philosophy, ethics. 3 CFU, 20 hours
Presentation of the course
Introduction to AI (Artificial Intelligence) from the point of view of the differences between biological and artificial intelligent systems. Logic, GOFAI (Good Old Fashion Artificial Intelligence - the old Artificial Intelligence models), strong and weak AI, Turing Test. Machine learning. AI philosophy. Ethical implications.
Examination program for attending and non-attending students
Teaching unit A
· "ARTIFICIAL INTELLIGENCE - Vol.2, a modern approach", 2nd edition, by Peter Norvig and Stuart Russel, published by Pearson
· Lecture notes by the teacher
· Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements
· Teaching unit B
· Lecture notes by the teacher
· Other material communicated from time to time in class
Warning
National and international students or Erasmus incoming are invited to make timely contact with the course professor.
The examination procedures for students with disabilities and/or with DSA must be agreed with the teacher, in agreement with the competent Office.
Prerequisites for admission
basic knowledge of statistics and basic logic. Familiarity with computer systems. Basic knowledge of algorithms and mathematical expressions related to the representation of functions.
Teaching methods
Theoretical and practical lessons
Teaching Resources
· "ARTIFICIAL INTELLIGENCE - Vol.2, a modern approach", 2nd edition, by Peter Norvig and Stuart Russel, published by Pearson
· Lecture notes by the teacher
· Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements
· Teaching unit B
· Lecture notes by the teacher
· Other material communicated from time to time in class
· Lecture notes by the teacher
· Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements
· Teaching unit B
· Lecture notes by the teacher
· Other material communicated from time to time in class
Assessment methods and Criteria
Written + oral: The exam consists of a written test and an oral test both mandatory. The written exam involves the design and development of a software project related to the topics covered during the course (development of an artificial intelligence system). The oral exam will consist of an interview on the program topics and on the project, aimed at ascertaining that the student has taken the test independently and has acquired the required knowledge and skills.
The exam is the same for attending and non-attending students.
The exam is the same for attending and non-attending students.
Unita' didattica A
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours
Unita' didattica B
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours
Professor(s)
Reception:
Wednesday 11 am, also via Skype or Teams (contact me via e-mail)
Via Teams, Skype or in Via Festa del Perdono 7, Dipartimento di Filosofia, cortile Ghiacciaia, secondo piano (please, take an appointment via e-mail)