First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
COGNITIVE PSYCHOLOGY AND PSYCHOBIOLOGY
Course unit
ARTIFICIAL INTELLIGENCE
PS02103965, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2015/16

Information on the course unit
Degree course First cycle degree in
COGNITIVE PSYCHOLOGY AND PSYCHOBIOLOGY
PS1082, Degree course structure A.Y. 2015/16, A.Y. 2017/18
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination ARTIFICIAL INTELLIGENCE
Department of reference Department of General Psychology
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge MARCO ZORZI M-PSI/01
Other lecturers ALBERTO TESTOLIN M-PSI/01

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses M-PSI/01 General Psychology 6.0

Mode of delivery (when and how)
Period Second semester
Year 3rd Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 6.0 42 108.0 No turn

Calendar
Start of activities 26/02/2018
End of activities 01/06/2018

Syllabus
Prerequisites: The topics discussed in the second part of the course are also covered, in a different way, in the courses “General Psychology” and “Neuropsychology”. Knowledge of the content of these courses is required an introduction to the study of connectionist models of cognition. Computer literacy is also required.
Target skills and knowledge: The course presents theory and practice of connectionist modelling with artificial neural network. The discussion of various types of neural networks and learning algorithms is followed by examples of application to the cognitive (neuro)sciences for modelling cognitive functions in both normal and pathological states.
Examination methods: Type of exam: written
Modality: multiple choice questions and open questions
Assessment criteria: The evaluation is based on the understanding of course topics and on the acquisition of the proposed concepts and methodologies
Course unit contents: Neural networks: basic elements. Learning algorithms. Simulation as a research method. Connectionist models of normal and impaired cognitive functions.
Planned learning activities and teaching methods: Teaching is based on frontal lectures covering the theory and practice classes on neural network modelling.
Additional notes about suggested reading: Other obligatory study material that will be available on the course Moodle (https://elearning.unipd.it/dpg/):
- Slides of the lectures
- Zorzi M. (2006). “Dai neuroni al comportamento: La simulazione dei processi cognitivi con modelli generativi”. Sistemi Intelligenti, 18(1), pp. 115-124.
- Zorzi M. (2006) “L’approccio computazionale in psicologia cognitiva”. Giornale Italiano di Psicologia, 23(2), pp. 225-245.
Textbooks (and optional supplementary readings)
  • Girotto V. e Zorzi M. (a cura di), Manuale di Psicologia Generale. Bologna: Il Mulino, 2016. capitolo 11 "Apprendimento e memoria nelle reti neurali" di M. Zorzi Cerca nel catalogo
  • Floreano D., Mattiussi C., Manuale sulle reti neurali. Bologna: Il Mulino, 2002. Il volume non è reperibile nelle librerie perchè fuori catalogo, ma per questo motivo può essere fotocopiato (vedi bibioteca di psicologia) Cerca nel catalogo
  • Bisiacchi P., Vallesi A (a cura di), Il cervello al lavoro. Nuove prospettive in neuropsicologia. Bologna: Il Mulino, 2017. capitolo 4: "Modelli computazionali e simulazione dei processi neuro-cognitivi" di M. Zorzi