Inserire una breve descrizione delle modifiche fatte
(Richiesto)
Minor changes are by default collapsed in the page history.
No changes
The page does not exist yet.
Failed to load changes
Version by on
Leave Collaboration
Are you sure you want to leave the realtime collaboration and continue editing alone? The changes you save while editing alone will lead to merge conflicts with the changes auto-saved by the realtime editing session.
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.
contenuti
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
testi / bibliografia
The bibliography is made available through the course web site.
metodi didattici
Lessons with slides
Lab activity
modalità di verifica e valutazione dell'apprendimento
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
Intelligent Systems Engineering 2025/2026 • 
