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Intelligent Systems

A.Y. 2018/2019
6
Max ECTS
48
Overall hours
SSD
INF/01
Language
English
Learning objectives
The course presents methodologies and technologies to implement intelligent systems for information and knowledge processing, i.e., systems which behaves similarly to the brain by using computational intelligence approaches. In particular, the course will presents the main approaches: neural networks, fuzzy systems, and evolutionary computing.
Expected learning outcomes
Theoretical foundation and practical use of the main computational intelligence approaches (neural networks, fuzzy systems, and evolutionary computing).

Lesson period: First semester

Lessons timetable

Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi

Exams calendar

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Course syllabus and organization

Linea Milano - disponibile in streaming da Crema

Responsible
Piuri Vincenzo
Lesson period
First semester
Course syllabus
· Neural networks: Definitions. Neurons: structures, perceptrons, RBF. Neural topologies: feed-forward, feedback, SOM. Learning: supervised, unsupervised. Performance. Optimization. Classification and clustering. Associative memories. Prediction. Function approximation. Applications.
· Fuzzy logic and systems: Fuzzy sets. Membership functions. Fuzzy rules. Defuzzification. Fuzzy reasoning. Fuzzy systems. Rough sets. Performance. Applications.
· Evolutionary computing: Genomic representation. Fitness functions. Selection. Genetic algorithms. Genetic programming. Evolutionary programming. Evolutionary strategies. Differential evolution. Swarm intelligence. Artificial immune systems.
· Hybrid systems
Website
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Piuri Vincenzo
Professor(s)