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SOFT COMPUTING

CODE 105144
ACADEMIC YEAR 2022/2023
CREDITS
  • 6 cfu during the 1st year of 9011 MATEMATICA(LM-40) - GENOVA
  • 6 cfu during the 2nd year of 9011 MATEMATICA(LM-40) - GENOVA
    		•
    SCIENTIFIC DISCIPLINARY SECTOR MAT/08
    TEACHING LOCATION
  • GENOVA
    		•
    SEMESTER 2° Semester
    TEACHING MATERIALS AULAWEB

    OVERVIEW

    Soft Computing introduces a set of Artificial Intelligence computational techniques which are based on the emulation of biological processes.

    In particular, we will introduce neural networks mimicking human brain skills to learn and generalize, evolutionary computation mimicking adaptation of biological species to their own environment, and swarm intelligence based on the model of intelligent cooperative behavior of some animals. A specific computer exercise, in MATLAB environment, is foreseen for each topic.

    The lectures will be held in person.

    AIMS AND CONTENT

    AIMS AND LEARNING OUTCOMES

    The general objective of the module is to provide students with computational techniques, based on the emulation of successfull biological processes, for the solution of classification, clustering, optimization and forecasting problems. In particular, specific objectives are aimed at the acquisition of knowledge and skills in the field of:

    • Supervised and unsupervised learning techniques for classification, clustering and prediction problems (neural networks);
    • Global optimization techniques (evolutionary computing, swarm intelligence)

     

    PREREQUISITES

    All topics are addressed in a self-consistent manner

    TEACHING METHODS

    The module includes lectures and three computer exercises

    SYLLABUS/CONTENT

    Neural networks

    • Introduction
    • Single- and Multi-layer perceptron
    • Recurrent Neural Networks
    • Self-Organizing Maps

    Evolutionary computation

    • Introduction
    • Genetic algorithms
    • Evolutionary algorithms

    Swarm Intelligence

    • Particle Swarm Optimization
    • Ant Colony Optimization

    RECOMMENDED READING/BIBLIOGRAPHY

    Lectures notes will be provided

    TEACHERS AND EXAM BOARD

    Exam Board

    Anna Maria MASSONE (President)

    SABRINA GUASTAVINO

    LESSONS

    LESSONS START

    In accordance with the academic calendar approved  by the Consiglio di Corso di Studi.

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    Three computer exercises will take place for which deadlines will be set. Positive assessment will be required for admission to a final oral exam

    ASSESSMENT METHODS

    Computer exercises are aimed at testing the practical skills acquired for the solution of the posed problems. They will be evaluated on the basis of the following criteria:

    • accuracy and optimization of the code
    • accuracy and presentation of the results (images, graphs, tables ...)
    • comments on the procedures followed and on the results obtained

    The oral exam is finally aimed at assessing the ability to communicate the knowledge acquired in a clear and competent manner

    FURTHER INFORMATION

    Students with DSA certification ("specific learning disabilities"), disability or other special educational needs are advised to contact the teacher at the beginning of the course to agree on teaching and examination methods that, in compliance with the teaching objectives, take account of individual learning arrangements and provide appropriate compensatory tools.