INTELLIGENZA ARTIFICIALE E LABORATORIO

Academic Year 2016/2017 - 1° Year - Curriculum Data Science
Teaching Staff Credit Value: 9
Scientific field: INF/01 - Informatics
Taught classes: 36 hours
Term / Semester:

Learning Objectives

  • 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

  • LABORATORIO

    The Laboratory focuses on the design and develop of several and different algorithms for complex problem solving. The goal of the laboratory is to provide to each student a deep and excellent knowledge on the several Artificial Intelligence search algorithms, included the feature basics of the natural computing algorithms.


Detailed Course Content

  • Artificial Intelligence

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

    Contenuti dettagliati del Corso:

    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 and Reasoning

    • Logical agents and puzzles
    • First order logic
    • Inferences
    • Utility and value of information
    • Simple and Complex decision making

Textbook Information

  • 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.