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--- teaching:is:main_is [2025/05/28 09:22] – [Slides & Reference Material] Franconi Enrico
+++ teaching:is:main_is [2025/06/22 16:12] (current) – [Final Exam] Franconi Enrico
@@ Line 112: / Line 112: @@
        * [[http://www.inf.unibz.it/~franconi/teaching/artint.info/code/ailog/ailog_code/ch05/elect_abd.ail|elect_abd.ail]] electrical wiring example with abduction; Example 5.31 in [[http://www.inf.unibz.it/~franconi/teaching/artint.info/html/ArtInt_133.html|Section 5.6]] */
        * Exercises: [[http://www.inf.unibz.it/~franconi/teaching/artint.info/html/ArtInt_137.html|5.5, 5.6, 5.7]]  ([[teaching:is:diag-rules-solutions|solutions]])
-* <color #22b14c>LAB 8</color>: Planning with Certainty
+* <del><color #22b14c>LAB 8</color>: Planning with Certainty</del>
   * Do {{ :teaching:is:ex_strips.pdf |Practice Exercise 8.A}} and {{ :teaching:is:ex_csp_planning.pdf |Practice Exercise 8.B}} /* ({{ :teaching:is:ex_strips_sol.pdf |Practice Exercise 8.A solution}} and {{ :teaching:is:ex_csp_planning_sol.pdf |Practice Exercise 8.B solution}}). */
   * Using the {{ :teaching:is:stripstocsp.jar.zip |STRIPS-to-CSP applet}} exercise with the coffee delivery problems (simple and complete) pre-loaded on the applet - [[https://aispace.org/strips_to_csp/|tutorial]]
@@ Line 128: / Line 128: @@
        * [[http://www.inf.unibz.it/~franconi/teaching/artint.info/html/ArtInt_308.html|12.4,12.5,12.6]] (top-down derivation) with the [[https://artint.info/code/ailog/ailog_code/ch12/west.ail|knowledge base about rooms]]
        * [[http://www.inf.unibz.it/~franconi/teaching/artint.info/html/ArtInt_308.html|12.8,12.9,12.14]] (SLD-resolution with functions) /*do also 12.15*/
-       /* * ([[teaching:is:ind-solutions|solutions]]) */
+       * ([[teaching:is:ind-solutions|solutions]] to all exercises)
 =====Final Exam=====
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 No "mock" exam paper is provided, given the quite simplifying specifications given above.
+**Modular Course**
+This course, //Foundations of Artificial Intelligence//, is the module 1 within the //Artificial Intelligence// course, which includes also the module 2 //Machine Learning in Practice//.
+There is formally a unique final exam for the //Artificial Intelligence// course: the exam covers the topics addressed in //module 1// and //module 2// and consists of two parts, one for each module, and each one counting 50% of the final grade. In order pass the exam, the students should get at least 18/30 in each part. A student may take the two parts of the exam in different sessions; a positive evaluation of one part remains valid for all three regular exam
+sessions of the academic year.