75836 - Theories and Systems of Artificial Intelligence (1)

Learning outcomes

What is Artificial Intelligence Problemns representation Problem solving: blind search algorithms and euristic algorithms Planning.

Course contents

The course deals with the main topics of artificial intelligence, starting from a historical and theoretical point of view up to present-day applied and technical issues of the discipline. Issues concerning the epistemology of artificial intelligence and cognitive science are topics of the course as well.

This is a basic course and does not require previous knowledge of the fields related to its main topics.

Relevant topics of the course will be the evolution of the notions of intelligence and artificial intelligence through XX and XXI centuries, with special reference to rationality, decision theory, language understanding, related philosophical subjects, cognitive modeling, the psychological framework of research, different methodologies of studying mental processes, neuroscience debate, and robotics in connection with AI and cognitive science.

The course is temporally divided into four parts:

1) The birth and the developments of artificial intelligence.

2) Problem solving and automated planning.

3) Knowledge representation and recent trends of artificial intelligence.

4) Epistemological issues of artificial intelligence, cognitive science and robotics.

Readings/Bibliography

Mandatory textbooks

- M. Marraffa, Percezione, pensiero, coscienza. Passato e futuro delle scienze della mente, Rosenberg & Sellier, Torino, 2019.

- S. Russell, P. Norvig, Artificial Intelligence: A modern Approach, Pearson, 4th edition, 2020 (chapters 1, 2, 3, 4, 7, 8, 9, 10, 11, 26, 27, 28).

Suggested readings:

- N. Bostrom, Superintelligenza. Tendenze, pericoli, strategie, Bollati Boringhieri, 2018. [The English version is also available.] 

- M. Marraffa, A Paternoster, Persone, menti, cervelli, Mondadori, Milano, 2012.

- G. Primiero, On the Foundations of Computing, Oxford University Press, Oxford, 2020.

- F. Rossi, Il confine del futuro. Possiamo fidarci dell'intelligenza artificiale, Feltrinelli, Milano, 2019.

- G. Tamburrini, Etica delle macchine. Dilemmi morali per robotica e intelligenza artificiale, Carocci, Roma, 2020.

Further readings will be mentioned during the course.

One more book among suggested readings is mandatory for not attending students.

Teaching methods

Lectures. Debates on main topics. Personal or group presentations on a subject agreed with professor will be possible.

Classes will be in person.

Assessment methods

Student will be tested through an oral examination in which s/he will face general subjects of artificial intelligence and specific subjects of fields involved in this disciplinary approach. The knowledge of the topics of the course and the capability of using them autonomously will be taken into consideration, together with the ability in producing personal remarks on the contents developed during the lessons. If it will be possible, students will be required to apply the main concepts in simple exercises.

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In particular, the achievement of the following targets will have a growing weight:

1) the completeness of the basic knowledge strictly connected to the program;

2) the appropriateness of the specific language;

3) the capability of personally re-using concepts learned during the course;

4) the capability to manage interdisciplinary reflections and argumentations;

5) the capability to apply the subjects to specific research cases and to produce autonomous and original remarks.

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1) and 2) are the lowest targets for the pass mark (18-22).

3) could give a fair evaluation, the more being so the less the learned knowledge will be mnemonic (23-26).

4) is for a good outcome (27-29).

5) is for an excellent one (30 or 30 with distinction).

Teaching tools

Slides and digital contents will be used during classes.

Office hours

See the website of Francesco Bianchini