Introduction to main principles and methods in Artificial Intelligence. The role of Intelligent Agents, planning and acting in the real world.

01. Introduction to AI
 01.01 History and foundations
  01.02 Overview of the problems tackled in AI
  01.03 Main research areas and application fields

02. Intelligent Agents
   02.01 Principal architectures 
  
03 Problem solving
  03.01 State space and related problem solving methods
  03.02 Non-informed and informed search methods
  03.03 Local Sarch
  03.04 Adversarial search: games
  03.05 Exercises
  
04 Logic and reasoning
  04.01 Logical Agents
  04.02 Propositional Logic
  04.03 First-order Logic
  04.04 Knowledge-based systems
  
05 Uncertainty in knowledge representation and reasoning
   05.01 Probabilistic Reasoning
   05.02 Bayesian Network
   05.03 Markov Decision Process
   05.04 Reinforcement Learning

06 Languages for Artificial Intelligence.
    06.01 Prolog: from logic to logic programming,
    06.02 Prolog programs as solvers
    06.03 Design and development of simple Prolog programs for inference and Java for agent reasoning cycle

There are no mandatory prerequisites. However, the Machine Learning course may help in understanding part whole picture provided in this course.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Teaching

Theory lectures and laboratory exercises, both in presence and online.

Attendance

Although strongly recommended, course attendance is not mandatory.

Course books

S. J. Russel, P. Norvig: "Artificail Intelligence: A modern approach", Prentice Hall, Last  or previous edition.

Assessment

The final exam consists of a written test, of duration of two hours, organized as a set of exercises and open questions choose by all the topics presented in the course. The total marks for the test sum up to 32 points, with a minimum threshold of 18/32 points; below the threshold the test is considered as "failed".

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

Materials from theory lectures and laboratory exercises.

Attendance

Same as attending.

Course books

Same as attending.

Assessment

Same as attending.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.