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Foundations of Artificial Intelligence (FoundAI)

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Official course presentation form

Open Learning Environment (OLE) web page


The official week-by-week Faculty timetable: lectures and labs of the course. Note that sometimes a LAB may be transformed into a LECTURE and vice-versa.

Office hours: anytime, by previous appointment by email to the lecturer (Enrico Franconi). In any case the lecturer is always available for the period after any lecture.

Some lectures and labs are offered online using Microsoft Teams. There is a video on how to start with Teams.

Language used in the course

  • Exclusively English.

A note on video-recording lectures (COVID-19 emergency)

Online lectures are video-recorded for the convenience of students. Students should switch off their video-camera. In any case, participation to a video-recorded online lecture indicates the student's consent to be included in the recording of the online lecture. Students can watch and use the the video-recorded online lectures only for learning purposes and for their exclusive personal use. Any other use, such as reproduction, distribution or sharing of the didactic material, is illegal.

All information concerning the personal data processing can be found under the following link:


Below you can download the relevant chapters of the book used in the various parts of the course.

Slides & Reference Material

The following is the standard material, it may be adjusted during the course.


  • LAB 1: Robot Control (applet) – Download Java if you need it from here.
  • LAB 2: Graph Searching with uninformed techniques (applet)
    • Manuals:
    • Explore with the search applet the Delivery Robot (Acyclic), the Delivery Robot (cyclic), the Vancouver Neighbourood, the Module 4 sample problem graphs: with Depth First, Breadth First, Lowest Cost First search strategies using different Neighbour Ordering Strategies; practice also with the quiz facility.
    • Do the Practice Exercise 3.B.
    • Exercise: practicing different search strategies with the graph in this slides (solution as a XML file for the applet)
    • Create your own problem graph for a delivery robot starting from a map with edge costs.
    • Create a problem graph for a simple problem chosen by you.
  • LAB 3: Graph Searching with Heuristics
    • Explore the Delivery Robot (Acyclic), the Delivery Robot (cyclic), the Vancouver Neighbourood, the Module 4 sample problem graphs: with Best First, Heuristic Depth First, A*, Branch and Bound search strategies, with or without Multiple-Path Pruning or Loop Detection, using different Neighbour Ordering Strategies. Explore also the behaviour with the abovementioned search graphs with potentially non terminating depth first strategies (e.g., Depth First or Heuristic Depth First) without cycle checking, and with loop detection or multiple path pruning.
    • Do the Practice Exercises 3.C, 3.D, 3.E.
    • Exercise: 3.4 (solution).
  • LAB 4: Constraints - Consistency
    • Explore with the CSP applet the sample problems: Simple Problem 1, Simple Problem 2, Scheduling Problem 1, Crossword Problem 1, Crossword Problem 2. These sample problems have been seen already in the course lectures; for the crossword problems, try to reconstruct the crossword graphical structure.
    • Do the Practice Exercises 4.A, 4.B.
    • Exercises: 4.2, 4.3 (only a,b), 4.5 - CSP and arc consistency (solutions).
  • LAB 5: Propositions and Inference
    • Getting started with AILog2, a representation and reasoning system for definite clauses, with declarative debugging tools.
      • Download the file, install and launch SWI Prolog, and load (consult) AILog2 in Prolog:
        • Windows: ?- consult("C:\\path-to-file\\").
        • Mac: ?- consult('/path-to-file/').
      • Go through the AiLog2 manual, from Section 1 to Section 6.
        • To load a knowledge base file from AILog2:
          • Windows: ailog: load 'C:\\path-to-kbfile\\kbfile.ail'.
          • Mac: ailog: load '/path-to-kbfile/kbfile.ail'.
    • Play with the elect_prop.ail electrical wiring example 5.7 from Section 5.3 of the book and the slides.
  • LAB 6: Debug, Diagnosis, Abduction
  • LAB 7: Planning with Certainty
  • LAB 8: Multiagent Systems and Games
    • xxx
teaching/is/main_is.txt · Last modified: 2022/06/23 06:20 by Franconi Enrico