ARTIFICIAL INTELLIGENCE

First cycle degree in PSYCHOLOGICAL SCIENCE

Campus: PADOVA

Language: English

Teaching period: First Semester

Lecturer: MARCO ZORZI

Number of ECTS credits allocated: 6


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 as introduction to the study of connectionist models of cognition. Computer literacy and basic notions of linear algebra are also required.
Examination methods: Type of exam: written.
Modality: multiple choice questions and open questions + paper assignment.
Paper assignment: Each student will be required to write a 3/4-page essay that will be assigned during the course and that must be hand over on the day of the written exam. The grade given to the paper will weight for 20% of the final score.
Course unit contents: Introduction to Artificial Intelligence. Artificial neural networks: mathematical formalism and general principles. Supervised learning: perceptron, delta rule, multi-layered networks and error backpropagation. Generalization and overfitting. Partially recurrent networks: learning sequential data. Unsupervised learning: associative memories and Hopfield networks, competitive learning, latent variable models, annealing, Boltzmann machines. Deep learning. Reinforcement learning. Computer simulation as a research method. Connectionis models of normal and impaired cognitive functions.