OVERVIEW

The course aims at studying  theory and practicalities of some formalisms for deductive AI, in particular knowledge representation and reasoning languages and tools and their application to discrete and mixed discrete/continuous planning/scheduling real problems.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims at studying some deductive reasoning techniques, and their applications to cope with real-world problems.

AIMS AND LEARNING OUTCOMES

- Study theory and practicalities of some formalisms for knowledge representation and reasoning

- Study how to model a problem using such formalisms

- Apply the competences and skills acquired on a concrete problem

PREREQUISITES

Concepts from previous courses of

- Artificial Intelligence
- Data base
- Information and Computation

in the Bachelor in Ingegneria Informatica and the same Master studies are the starting point of this course.

TEACHING METHODS

The course is organized as follows:

- Lectures (approx. 50%)
- Exercises and presentations (approx. 25%)

- Project set-up (approx. 25%)

SYLLABUS/CONTENT

- Database languages (re)introduction

- Deductive Artificial Intelligence:

- Knowledge Representation and Reasoning

- Answer Set Programming (ASP)
- Extended Planning Domain Definition Language (PDDL+)

- Applications to:
  ASP for (discrete) scheduling
  PDDL+ for (mixed discrete-continous) planning

RECOMMENDED READING/BIBLIOGRAPHY

All slides and exercises presented during the lectures will be made available on AulaWeb.

TEACHERS AND EXAM BOARD

Exam Board

MARCO MARATEA (President)

GUALTIERO VOLPE

ALESSIO MERLO (President Substitute)

LESSONS

LESSONS START

In the week 20-24 of September 2021

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam is made of a practical project.

ASSESSMENT METHODS

Project realization and presentation will be evaluated.

Exam schedule