Dipartimento di elettronica e informazione
Politecnico di Milano
Artificial Intelligence 2010-11
© Marco Colombetti, 2011
1. Introduction to the course
1.1 Course presentation
Two courses in parallel
! Artificial Intelligence, in English (Marco Colombetti, Mario Verdicchio, Viola Schiaffonati)
! Intelligenza artificiale, in Italian (Francesco Amigoni, Nicola Gatti, Viola Schiaffonati)
Program
! Introduction: goals, research areas, applications
! Representations: iconic vs. symbolic
! Iconic-based methods:
! State space search: uninformed and informed search methods
! Constraint satisfaction problems
! Symbolic-based methods:
! Logic: knowledge representation in First Order Logic
! Planning: Situation Calculus, STRIPS, plan space search
! Philosophical foundations
Textbook
! S. Russell, P. Norvig, 2010. Artificial Intelligence: A modern approach, 3rd ed., Prentice-
Hall/Pearson (1,132 pages)
! Textbook’s web site available at http://aima.cs.berkeley.edu/
! Parts covered by the course (for a total of 318 pages):
! Part I: Artificial Intelligence. Chapters 1 and 2 (pages 1–63)
! Part II: Problem solving. Chapters 3 and 6 (pages 64–119 and 202–233)
! Part III: Knowledge, reasoning, and planning. Chapters 7–10 (pages 234–400)
! Additional lecture notes downloadable from the course’s website (see below)
Final examination
! A written test, 2 hours, with conceptual questions and exercises.
Further details
! The Logic module is given by Mario Verdicchio, the two lessons on Philosophical foundations by
Viola Schiaffonati, the rest by Marco Colombetti
! Marco Colombetti:
! office hours: Thursday 14:30–16:00 (Department of Electronics and Information, 1st floor,
ext. 3686)
! home page: http://www.dei.polimi.it/people/colombetti/
! email: marco.colombetti@polimi.it – please send messages from the official student
address
! course website: http://home.dei.polimi.it/colombet/AI/
Marco Colombetti Artificial Intelligence 2010-11: 1. Introduction 2
1.2 About AI
The birth of Artificial Intelligence
Artificial Intelligence (AI):
! officially born in 1956, during a summer seminar at Darthmouth College (Hanover, New
Hampshire), attended by John McCarthy, Marvin Minsky, Allen Newell, Nathaniel Rochester,
Claude Shannon, Herbert Simon (later Nobel Prize for Economics), and others
Goals:
! design and implement computer-based systems that exhibit intelligent behaviour
! understand intelligence as a computational processes
The context in 1956:
! computers are huge, awfully expensive, brittle, with very little computing power, still perceived
as number-crunching machines
! still no high-level programming languages (apart from the first version of FORTRAN), no
dynamic data structures, no databases, no object-oriented programming, no software engineering,
...
! cognitive psychology is just beginning: thought is starting to be conceived as information
processing
What is an intelligent system?
Analysis of Intelligent(x):
! applicability conditions: for what values of x is the predicate meaningful?
! truth conditions: for what values of x is the predicate true?
As far as the applicability conditions are concerned, x has to be an agent, that is, a system capable of
autonomous action. The term “intelligent” is applied to agents, and by extension to their actions and
possibly to the results or products of their actions; examples:
! intelligent agents: John is intelligent, my dog is very intelligent, my car has intelligent
suspensions
! intelligent actions: it was intelligent of John not to run away after breaking the glass
! intelligent product: this is a very intelligent chair (in the sense that it has been intelligently
designed).
Being intelligent is not a simple concept (contrary to, for example, being a metal, or being a gas). As a
consequence, there will be no simple theory of intelligence. Maybe “intelligent” cannot even be turned
into a rigorous scientific term.
Among the typical features of intelligent organisms are:
! perception of the environment
! problem solving and rational action (mostly human, but also available to complex non-human
animals)
! learning
! sociality and communication
! language use (humans only)
What is an artificial intelligent system?
Why do we obviously assume that an artificial intelligent system will be a system controlled by a
suitably programmed digital computer?
Because digital computers are, in some sense, universal machines: given that cognitivism assumes that
thought processes are just computations, digital computers can implement thought processes.
Marco Colombetti Artificial Intelligence 2010-11: 1. Introduction 3
Main research areas
! “core” AI: problem solving, knowledge representation, reasoning
! natural language processing
! machine learning
! computer vision
! robotics
Main application areas
! expert systems
! planning and scheduling
! optimisation
! language technologies
! semantic web
! multiagent systems
! data mining
! industrial robotics
! ...
1.3 Some AI-related courses at Politecnico di Milano (Leonardo Campus)
! Soft computing: neural networks, fuzzy models, genetic algorithms (Italian)
! Autonomous agents and multiagent systems
! Data mining and text mining
! Image analysis and synthesis
! Videogame Design and Programming
! Ingegneria della conoscenza (modelli semantici): semantic modelling and reasoning for the
Semantic Web (in Italian)
! Robotica, Robotica 2: robotics (in Italian)
! Elaborazione del linguaggio naturale: natural language processing (in Italian)
! Tecniche di apprendimento automatico per applicazioni di data mining: machine learning and
data mining (in Italian)
! Temi filosofici dell’informatica: philosophical issues in Computer Science (in Italian)
