General information

Subject type: Mandatory

Coordinator: Rosa Herrero Antón

Trimester: Third term

Credits: 4

Teaching staff: 

Sandra Obiol Madrid

Teaching languages

  • Catalan

The subject will be taught in Catalan. Students will be able to address the teacher in the language that is most comfortable for them.

Some content, transparencies and bibliography will be in English.


Basic skills
  • B2_That students know how to apply their knowledge to their job or vocation in a professional way and have the skills they demonstrate by developing and defending arguments and solving problems within their area of ​​study

  • B3_Students have the ability to gather and interpret relevant data (usually within their area of ​​study), to make judgments that include reflection on relevant social, scientific or ethical issues

  • B5_That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy

Specific skills
  • EFB3_Ability to understand and master the basic concepts of discrete mathematics, logic, algorithms and computational complexity, and their application for solving engineering problems

Transversal competences
  • T1_That students know a third language, which will be preferably English, with an adequate level of oral and written form, according to the needs of the graduates in each degree

  • T2_That students have the ability to work as members of an interdisciplinary team either as one more member, or performing management tasks in order to contribute to developing projects with pragmatism and a sense of responsibility, making commitments taking into account the available resources


Artificial intelligence is a discipline that studies intelligent agents, understanding as such those devices (software and / or hardware) that perceive the environment, reason and take action to achieve their goals. In recent years artificial intelligence has hit the industry with great force and many analysts believe it will be the main factor in the upcoming industrial revolution.

During the course there is an introduction to the most classic Artificial Intelligence with an in-depth study of the search and logic algorithms that are used today to solve countless problems. For example: google search, google maps, Amazon and Netflix recommending systems, making schedules, autonomous vehicles, video games, and a long etc. The last chapter gives a brief introduction to machine learning, more specifically to the classification and clustering that are the basis of data analysis algorithms.


1 Introduction to Artificial Intelligence    
    1.1 History
    1.2 Applications
    1.3 Ethics and feminism
2 Troubleshooting    
    2.1 Troubleshooting
    2.2 Uninformed search: BFS, DFS
    2.3 Informed search: voracious search, algorithm A
    2.4 Heuristic functions
    2.5 Search in games: minimax, alpha-beta prunning
    2.6 Satisfaction of restrictions
3 Logic    
    3.1 Representation of knowledge: facts and rules
    3.2 Inference or reasoning algorithms
4 Machine learning    
    4.1 Supervised. Classification: N-nearest neighbors, decision trees, Naive Bayes
    4.2 Unsupervised. Clustering: K-means

Evaluation system


  • PR_E: Individual written test. Weighting of the final grade 60% if the grade is> = 5
  • PRAC: internships from 1 to 4. Weighting in the final grade 40% (each 10%) if a minimum of two internships have been approved

Final grade calculation (NF):

  • Si PR_E >= 5 and 2 or more approved internships : NF = PON = PR_E 0,60 + PRAC 0,40 
  • If PR_E < 5 or not 2 approved practices: NF = min (PR_E, PON)


  • The written test (PR_E) can be retrieved. The final grade will be calculated as set out above with the written test recovery grade.


  • Attendance at internships is mandatory. If a student does not attend an internship session he will be graded with a grade of 0 (zero) in the corresponding internship
  • Following UPF regulations, if it is detected that a practice or a written test has been copied from a classmate, the mark will be 0 (zero) for both what has been copied and what has been allowed to be copied.
  • In order for the student to be entitled to recovery he / she must have taken the written test



Russel, Stuard and Norvic, Peter (2013), "Artificial Intelligence: a moderate approach". (3rd edition) Prentice Hall.