Ateneo - UPO

Fundamental principles and methodologies of intelligent systems based on knowledge representation and reasoning; in particular, systems based on logical rules, ontologies and knowledge graphs, planning systems, constraint reasoning, integration of different automated reasoners

Artificial Intelligence: a Moden Approach. Fourth Edition. Peter Norvig, Stuart Russel, PEARSON.

Knowledge and comprehension: the fundamentals of intelligent knowledge-based systems.
Capability to apply knowledge and comprehension: the ability to apply the intelligent knowledge-based systems to real-world problems, related to the domains considered in the course of study.
Autonomy of judgment: judging the appropriateness of the different systems, methodologies and formalisms for managing real-world real-world real-world real-world problems
Communication skills: ability to explain, both on a technical and non-technical level, the solutions proposed for problems assigned during the course.
Learning skills: exercise the ability to study independently by reading in-depth documentation on the topics of the course

Mathematical background required to enter the master degree.

Lectures, exercises.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Oral examination with question on different topics, and a presentation on a topic among the ones proposed by the lecturers. The evaluation measures the proportion of achievement of the learning objectives.

Basic concepts in mathematical logic. Knowledge representation and reasoning with logical rules, ontologies, knowledge graphs. Constraint reasoning, declarative problem solving, answer set programming.
Decision support: knowledge acquisition and representation, inferential techniques. The temporal dimension: problems and temporal reasoning methodologies.
Classical planning and State-space search. Hierarchical planning, planning in a non-deterministic world.

Knowledge: knowledge of the fundamental principles and methodologies of intelligent systems based on knowledge, and in particular for systems based on logical rules, ontologies and knowledge graphs, planning systems, integration of different automated reasoners. Competence and ability: given real problems, the ability to evaluate the adequacy of the systems and methodologies studied to solve them and to select and apply the most appropriate systems and methodologies to such problems. Autonomy of judgement: judging the appropriateness of different systems, methodologies and formalism for real-world problems Communication: ability of illustrating solutions both for a technical and a non-technical audience. Learning: ability of studying material proposed for essays.