Università telematica internazionale UNINETTUNO

Computer Engineering (Academic Year 2019/2020) - Programming and security

Intelligenza artificiale


Lesson n. 1: Intelligenza Artificiale. Introduzione

   What is AI

   Foundations of AI

   History of AI
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Lesson n. 2: Agenti intelligenti
   Agents and Environments

   The Nature of Environments

   The Structure of Agents
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Lesson n. 3: Searching
   Example problems

   Tree search and graph search

   Uninformed search
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Lesson n. 4: Informed search - Ricerca con Informazione
   Greedy search

   A* search

   Heuristic functions

   Local Search
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Lesson n. 5: Constraints satisfaction problems - Soddisfacimento di vincoli
   Definition of CSP

   Constraint Propagation

   Search in CSP

   Structure of CSP
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Lesson n. 6: Logica proposizionale
   Logical Agents

   Logic, Formally

   Propositional Logic

   Theorem Proving

   Special CNF Systems

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Lesson n. 7: Logica del primo ordine
   Semantic & Syntax


   Numbers, Sets, Lists
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Lesson n. 8: Inferenza in logica del primo ordine
   Reducing to propositional inference


   Forward chaining

   Backward chaining

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Lesson n. 9: Planning - Pianificazione

   Complexity of Planning

   Algorithms for Planning

   Heuristics for Planning

   The Planning Graph
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Lesson n. 10: Applicazioni del planning
   Planning And Scheduling

   Critical Path Method

   Hierarchical Planning

   Planning in Other Domains
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Lesson n. 11: Quantificazione dell’incertezza



   Bayes’ Theorem
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Lesson n. 12: Reti Bayesiane
   Introduction to Bayesian Networks

   Conditional independence in BN

   Exact Inference

   Approximated Inference
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Lesson n. 13: Probabilistic reasoning over time
   Time and uncertainty

   Four tasks of temporal models

   Hidden Markov Models

   Kalman Filters

   Dynamic Bayesian Networks
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Lesson n. 14: Making simple decisions
   Utility Theory

   Decision Networks

   The Value of Information
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Lesson n. 15: Complex decision making - Prima parte
   Sequential Decision Problems

   The Bellman Equation

   Partially Observable Markov Decision Processes
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Lesson n. 16: Complex decision making - Seconda parte
   Decisions With Multiple Agents

   Dominance and Equilibrium

   Mechanism Design and Auctions
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Lesson n. 17: Apprendimento & alberi di decisione
   Forms of Learning

   Supervised Learning

   Decision Trees
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Lesson n. 18: Regressione e classificazione - Prima parte
   Linear Regression

   Linear Classification

   Logistic Regression

   Neural Networks
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Lesson n. 19: Regressione e classificazione - Seconda parte
   Support Vector Machines

   Non Parametric Models

   Nearest Neighbor

   Non Parametric Regression

   Ensamble Learning

   Computational Learning Theory
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Lesson n. 20: Learning with knowledge & statistical learning
   Knowledge in learning

   Learning with background

   Statistical learning with complete knowledge

   Statistical learning with uncomplete knowledge
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