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Mandatory course of second year of the Master Degree in Computer Engineering. |
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The course has the objective to describe methodologies of the artificial intelligence. In particular, will be discussed the concept of intelligent agent, knowledge representation, inference, deduction and machine learning. |
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The course gives 9 credits and it is composed of 20 hours of video lectures. Video lectures present the following concepts:
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Artificial Intelligence. Introduction
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Intelligent Agents
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Searching
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Informed search
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Constraints satisfaction problems
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Propositional Logic
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First Order Logic
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Inference in First Order Logic
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Planning
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Planning in the real world
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Quantifying uncertainty
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Bayesian Networks
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Probabilistic reasoning over time
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Making simple decisions
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Complex decision making. First part
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Complex decision making. Second part
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Learning & decision trees
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Regression and classification. First part
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Regression and classification. Second part
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Learning with knowledge & statistical learning
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S. J. Russell, P. Norvig, “Artificial Intelligence. A Modern Approach.”, Pearson, Milano
T. Mitchell - "Machine Learning"
S. Haykin, “Neural Networks - A comprehensive foundation”, Prentice-Hall |
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During the lectures there are several exercises to be done at home. |
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Professor/Tutor responsible for teaching
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Prof.
Giovanni Felici
- Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti” - CNR (Roma - Italia)
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