|SCIENTIFIC DISCIPLINARY SECTOR
The course introduces to the main themes of deductive-based Artificial Intelligence.
AIMS AND CONTENT
The goal of the course is to provide the foundations of knowledge-based intelligent autonomous agents.
AIMS AND LEARNING OUTCOMES
The course introduces the languages and the techniques through which intelligent agents can operate autonomously on a deductive basis. The aim of the course is to provide students with the capability of formalizing domains of interest in order to treat them in the context of autonomous intelligent agents, with specific reference to propositional logics, first-order logics, description logics, and automated planning languages. The main result is the student's ability to frame the problems in a formal way and abstract their main features in a specification which makes computationally feasible to implement autonomous agents.
Some preliminary knowledge of combinatorics, algebra and theoretical computer science are useful for a better understanding of the course material.
Lectures (possobly recorded) for the theory part; practical sessions with the teacher to solve assigned exercises (possibly online)
Propositional logic: syntax, semantics, propositional knowledge bases, normal forms, inference procedures.
First-Order Logic: representation, syntax and semantics, knowledge engineering, inference procedures.
Classical Planning: definition, PDDL language, examples, planning as state-space search.
Stuart Russell, Peter Norvig - Artificial Intelligence, a Modern Approach (third edition) - Prentice Hall
TEACHERS AND EXAM BOARD
ARMANDO TACCHELLA (President)
RENATO UGO RAFFAELE ZACCARIA (President Substitute)
L'orario di tutti gli insegnamenti è consultabile all'indirizzo EasyAcademy.
Test with open and closed questions.
Ability to formalize domain of practical interest and solve them using the techniques shown in the course.