93669 - Intelligent Systems Engineering

Course Unit Page

  • Teacher Andrea Omicini

  • Learning modules Andrea Omicini (Modulo 1)
    Giovanni Ciatto (Modulo 2)

  • Credits 6

  • SSD ING-INF/05

  • Teaching Mode Traditional lectures (Modulo 1)
    Traditional lectures (Modulo 2)

  • Language English

  • Campus of Cesena

  • Degree Programme Second cycle degree programme (LM) in Computer Science and Engineering (cod. 8614)

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Industry, innovation and infrastructure

Academic Year 2022/2023

Learning outcomes

At the end of the course, students get acquainted with the fundamental issues of intelligent systems, the most relevant computational models and technologies, and the most effective methods. In particular, students become familiar with the fittest solutions, languages, technologies, architectures, and methodologies to design intelligent systems, and are capable of - devising the problems requiring artificial intelligence techniques for their solution; - determining the most proper conceptual and methodological approaches; - selecting and integrating the fittest technologies for implementing the solutions detected.

Course contents

• Intelligence and autonomy in software and artificial systems

  • Artificial intelligence: short history, main concepts and techniques
  • The many diverse meanings of autonomy in artificial and software systems

• Agents, multi-agent systems, and the engineering of intelligent systems

  • Agent meta-models, models, and main technologies
  • Agent-oriented software engineering

• AI meets autonomy: Intelligent agents

  • Logic & computation
  • Automated reasoning & planning
  • Reasoning agents

• Symbolic vs. sub-symbolic AI

  • Machine learning meets intelligent agents
  • eXplainable Artificial Intelligence

Readings/Bibliography

The bibliography is made available through the course web site.

Teaching methods

  • Lessons with slides
  • Lab activity

Assessment methods

The assessment of the learning achievements is organised around the development of an individual/group project, which results in the production of suitable artefacts, either documental or software.

The final test consists in the oral discussion of the project.

General guidelines for grades:

  • (18-23) good overall understanding of the main topics of the course; mostly-correct usage of technical and scientific language
  • (24-27) very good understanding of most of the topics of the course; proper usage of technical and scientific language
  • (28-30) deep understanding of all the topics of the course; brilliant usage of technical and scientific language
  • (30L) complete understanding of all the topics of the course, and beyond; outstanding usage of technical and scientific language

Teaching tools

Links to further information

http://apice.unibo.it/xwiki/bin/view/Courses/Series/Ise

Office hours

See the website of Andrea Omicini

See the website of Giovanni Ciatto