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.