Academic Year 2021/2022 - 2° Year - Curriculum Curriculum A - Clinico - Riabilitativo
Teaching Staff Credit Value: 12
Scientific field: INF/01 - INFORMATICS
Taught classes: 72 hours
Term / Semester:

Learning Objectives

  • History of Cognitive Science

    The course aims to provide critical knowledge about the history of cognitive science and the relationship between genetics and cognitive performance.

    The module is organised in three parts:

    1. The first is devoted to the epistemological bases of scientific knowledge (with special attention to the life sciences).

    2. The second section discusses – through a historical and critical path – the stages that led to the birth of cognitive science and to the "naturalization of the mind."

    3. The third part is devoted to a critical analysis of the main studies and theories that concern the question of genetic determinism and the relation between behaviour / genes / culture.

    The overall sense of the course is thus marked by three general questions: what are the epistemological assumptions to say that something is "scientifically proven"? what have been the main historical and theoretical stages that have shown a relationship between the intellectual and the anatomical and physiological structures of the organism? if the organic structures of an individual are due to its genetic heritage, does their behavioural performance depend on genes?

    The course will not give definite answers to these questions. The debate – at least on its most border aspects – is still ongoing. However, it will provide knowledge and critical tools to be able to better judge any theoretical or practical action related to these questions.

  • Artificial Intelligence

    Knowledge and understanding: Students will acquire basic knowledge about Intelligent Agents and their main features.
    Applying knowledge and understanding: students will be to able to apply the acquired knowledge in several fields such as: searching for solutions to hard combinatorial problems, games and decision theory, automated deduction and reasoning.
    Autonomia di giudizio (making judgements): Students will be able to evaluate the possibility of developing algorithms and intelligent systems to mechanize decisional processes in different application fields.
    Communication skills: students will acquire the necessary communication skills and appropriate linguistic skills to explain and clarify problems relative to intelligent systems and their applications.
    Capacità di apprendimento (learning skills): students will be able to adapt the acquire knowledge to new contexts as well and to understand the limits of applicability of artificial intelligence techniques

Course Structure

  • History of Cognitive Science

    Lessons and discussion in the classroom in the presence of the teacher.

    If the teaching is given in mixed mode or at a distance, due to the Covid emergency, the necessary variations may be introduced with respect to what has been stated previously, in order to respect the program foreseen and reported in the syllabus. The learning verification can also be carried out electronically, should the conditions require it.

Detailed Course Content

  • History of Cognitive Science

    1. The importance of a critical and epistemological approach to the study of the mind.

    2. Naturalization of cognitive processes. Evolution by natural selection.

    3. Instincts, behavioural patterns and optimality models.

    4. Genetics, neo-Darwinism, population genetics and sociobiology.

    5. The case of altruism: kin selection, reciprocity and individual strategies, game theory.

    6. The evolutionary function of emotions.

    7. The primacy of genetics?

    8. The limits of the genetic reductionism and the evolution in four dimension. The Brain That Changes Itself.

    9. Genes and culture: diversity and conflicts between genres: from the seductive strategies to the maximization of benefits.

  • Artificial Intelligence

    The course is divided into 2 main parts. First part on Problem Solving, and second part on Knowledge and Reasoning.

    FIRST PART: Problem Solving

    • Foundations and history of Artificial Intelligence
    • Intelligent Agents and classifications
    • Search and Problem Solving
    • Search in games
    • Constraint Satisfaction Problems
    • Search using Natural Computing Algorithms
    • SECOND PART: Knowledge, Reasoning and Learning

    • Logical agents and puzzles
    • First order logic and Inferences
    • Uncertainty and Probability
    • Decision making, Utility and value of information
    • Learning from examples

Textbook Information

  • History of Cognitive Science

    Di Nuovo, Prigionieri delle neuroscienze?, Giunti 2014

    Slides and lecture notes are available on the web platform Studium.

  • Artificial Intelligence

    Required textbook is Artificial Intelligence, a modern approach, 3rd Edition, S. Russel, P. Norvig. Other material will be provided by the instructor in class.