Esame completo di FOUNDATIONS OF ARTIFICIAL INTELLIGENCE per il corso di Computer Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
Esame completo di FOUNDATIONS OF ARTIFICIAL INTELLIGENCE per il corso di Computer Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
Qualità dell’importazione: il testo è stato estratto direttamente dal documento originale.
Passaggi rappresentativi riconosciuti nelle diverse parti del materiale. Il testo completo resta presente nella pagina per la ricerca, mentre l’anteprima compatta rende più semplice la lettura.
Politecnico di Milano School of Industrial and Information Engineering Foundations of Artificial Intelligence February 6, 2024 Prof. Francesco Amigoni & Prof. Pierluca Lanzi GENERAL INSTRUCTIONS • This is a closed-book/closed-notes exam. Notes, books, and mobile phones are not allowed. Pencils are not allowed. Answers must be written inside the answer boxes designated for each problem. Answers must be legible and adequately motivated. • The exam consists of XX sheets. The exam must be returned with all its original sheets. No sheet can be added. None of the sheets can be removed. Exams that are returned without all the sheets will not be graded. • Only non-programmable calculators are allowed. • If a student is caught using forbidden material, the exam will immediately end, and the disciplinary committee will be notified. • Exam receiving 5 points or less will be graded as REPEAT. SCORING • A problem left unsolved will amount to zero points. • Completely wrong answers assign negative points. STUDENTS HAVE 1:30h TO SOLVE ALL THE PROBLEMS SIGN THIS BOX TO WITHDRAW FROM THE EXAM FAMILY NAME FIRSTNAME CODICE PERSONA/ID Problem Scores /8 /8 /8 /8 Uncertainty. Question 1: Write the marginalization formula to compute 𝑃(𝑋=𝑥!) knowing the values of 𝑃(𝑋=𝑥! ⋀ 𝑌=𝑦", for all the values of 𝑥! and 𝑦". Answer: from the slides, Question 2: Write the chain rule for a Bayesian Network with n random variables X1, …, Xn Answer: from the slides, Uncertainty (Continued). Question 3: Consider the Bayesian Network in the previous page. Derive the formula to compute P(Letter = L0). Answer: two exams asked for P(L0) two for P(L1), in both cases the solution is included in the course slides, Question 4: Compute P(Letter = L0) with a 3-digit precision using the formula written to answer question…
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