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degree course in COMPUTER SCIENCE

Course year 2
Teaching units Unit Apprendimento ed evoluzione in sistemi artificiali
Information Technology (lesson)
  • TAF: Compulsory subjects, characteristic of the class SSD: INF/01 CFU: 6
Teachers: Marco VILLANI
Exam type oral
Evaluation final vote
Teaching language Italiano
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The course presents an approach to programming that differs fron the traditional one, and that is inspired by natural systems. It aims at developing systems that, by interacting with a suitable environment, can learn how to perform nontrivial tasks. Therefore learning, evolution and co-evolution in artificial systems will be discussed, by presenting different classes of systems, including neural networks, genetic algorithms and cellular automata. Applications will also be presented

Admission requirements

basic elements of computer science, mathematics and statistics, complying with the requirements listed in the website of the degree course

Course contents

Teaching takes place in the second semester of the second year, for a total of 48 hours of frontal teaching (6 CFU) divided between hours of "theory", ie lessons in which the topics of the course are introduced and illustrated, and hours of " laboratory ”, in which the ideas and methods presented are applied and new knowledge is acquired through" learning by doing ".

A list of contents could be as follows:

1. The classical approach to artificial systems. Natural vs. artificial systems. Self-organization in physics, biology and social science
2.Neural networks (Hopfield model, gradient backpropagation, SOM, other models)
3.Genetic algorithms. Classifier systems. A quick look at genetic programming
4. Cellular automata
5. Agent-based models
6. A quick look at artificial life

Teaching methods

Teaching is based, on an ordinary basis, on frontal lectures and exercises (including an optional project). Student questions and interventions are welcome and encouraged. Attendance is not compulsory, but strongly recommended. The course is delivered in Italian. All technical and organizational information on teaching, as well as teaching material, will be uploaded to the Dolly platform. The student is invited to register and consult this platform regularly

Assessment methods

written exam with open questions (2 questions chosen from 4-5 questions regarding the topics discussed in class, it is necessary to have a sufficient mark in both answers for the test to be sufficient). This test is aimed at verifying the learning of the main topics of the course and the reasoning skills acquired by the students, The students who have developed a project can request to be evaluated (1/3 of the total) on the basis of the report and of a short critical discussion

Learning outcomes

Knowledge and understanding
The student will learn the main concepts of adaptive and bio-inspired systems

Application of knowledge
Thanks to the wide range of different examples that will be considered, the student will be able to apply the methods that are best suited for different cases

Autonomous judgement
Thanks to the wide range of different examples that will be considered, the student will be able to identify the methods that are best suited for different cases, alongside with their limitations

Communication skills
The sudent will learn the language of complex systems science, and she will show her mastery in the written exam

Learning skills
The student will have gained an understanding of different approaches that will allow her to learn also methods that differ in some aspects from those that will have been taught


Gli argomenti verranno presentati su lucidi, che verranno resi disponibili agli studenti; alcuni libri (interessanti ma non indispensabili) verranno consigliati a lezione; altri materiali saranno messi a disposizione dal docente