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Artificial Intelligence Introduction

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Title: Artificial Intelligence Author: Luigi Last modified by: Luigi Ceccaroni Document presentation format: On-screen Show (4:3) Other titles: Arial ... – PowerPoint PPT presentation

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Title: Artificial Intelligence Introduction


1
Artificial IntelligenceIntroduction
  • Fall 2008
  • professor Luigi Ceccaroni

2
Instructors
  • Luigi Ceccaroni
  • Omega building - Office 111
  • luigi_at_lsi.upc.edu
  • Núria Castell Ariño
  • FIB building - Second floor
  • castell_at_lsi.upc.edu

3
Course description
  • This course introduces
  • Representations
  • Techniques
  • Architectures
  • This course also explores applications of
  • Rule chaining
  • Heuristic search
  • Constraint propagation
  • Constrained search
  • Decision trees
  • Knowledge representation
  • Knowledge-based systems
  • Natural-language processing
  • It accounts for 7.2 credits of work load,
    distributed as
  • 3.6 credits for theory
  • 2.4 for recitations
  • 1.2 for laboratory

4
Web pages
  • http//www.lsi.upc.es/bejar/ia/ia.html
  • http//www.lsi.upc.edu/luigi/MTI/AI-2008-fall/ai.
    html
  • http//raco.fib.upc.es/

5
Background
  • Students need the following knowledge (at the
    undergraduate level) to appropriately follow the
    course
  • English language
  • Propositional and predicate logic capacity to
    formulate a problem in logical terms
  • Logical inference strategies of resolution
    capacity to solve problems by resolution
  • Graph and tree structures algorithms for search
    in trees and graphs
  • Computational complexity calculation of
    algorithm execution's cost
  • There are assignments that expect students to be
    able to read and write basic Java. This is the
    only formal pre-requisite.

6
Aim of the course
  • The general objectives of the course can be
    summarized as
  • To identify the kind of problems that can be
    solved using AI techniques to know the relation
    between AI and other areas of computer science.
  • To have knowledge of generic problem-solving
    methods in AI.
  • To understand the role of knowledge in present
    IA to know the basic techniques of knowledge
    representation and their use.
  • To be able to apply basic AI techniques as
    support for the solution of practical problems.
  • To be able to navigate the basic bibliography of
    AI.

7
Topics
  • 1. Search
  • 1.1 Problem representation
  • 1.2 Search in state space
  • 1.3 Uninformed search
  • 1.4 Informed search (A,IDA, local search)
  • 1.5 Games
  • 1.6 Constraint satisfaction

8
Topics
  • 2. Knowledge representation and inference
  • 2.1 Methodologies for knowledge representation
  • 2.2 Rule-based systems
  • 2.3 Structured representations frames and
    ontologies

9
Topics
  • 3. Knowledge-based systems
  • 3.1 Definition and architecture
  • 3.2 Expert systems
  • 3.3 Knowledge engineering
  • 3.4 Approximate reasoning

10
Topics
  • 4. Natural language
  • 4.1 Textual, lexical and morphological analyses
  • 4.2 Levels of natural language processing
  • 4.3 Logical formalisms definite clause
    grammars
  • 4.4 Applications and current areas of interest

11
Topics
  • 5. Machine learning
  • 5.1 Decision trees

12
Bibliography
  • There are no required readings, apart from the
    course lecture notes. Additional reading can be
    found in the following text
  • Russell, Stuart J. and Peter Norvig
  • Artificial intelligence a modern approach. 2nd
    edition
  • Upper Saddle River, NJ Prentice Hall, 2002
  • ISBN 0137903952.

13
What is AI?
  • There is no single definition, but several
    approaches, that Russell-Norvig summarize in four
    main ones.
  • These approaches follow different points of view.
  • Their influences are diverse (Philosophy,
    Mathematics, Psychology, Biology...).
  • Their fields of application are ample and
    interrelated.

14
Approaches to AI
  • Systems that act like humans
  • The study of how to obtain that computers perform
    tasks at which, at the moment, people are better
    (Rich and Knight, 1991)
  • Systems that think like humans
  • The effort to make computers think... machines
    with minds in the full and literal sense
    (Haugeland, 1985)
  • Systems that think rationally
  • The study of the mental faculties through the
    study of computational models (Charniak and
    McDermott, 1985)
  • Systems that act rationally
  • The effort to explain and emulate the intelligent
    behavior in terms of computational processes
    (Shalkoff, 1990)

15
Other approaches to AI
  • Good Old-Fashioned Artificial Intelligence
    (GOFAI) (Douglas Lenat Cyc)
  • Cramming a computer full of knowledge about the
    real world and methods to manipulate it
  • Intelligence intimately tied up with having and
    being able to use knowledge
  • Its worth to go to school
  • Robotic insects example
  • Legs controlled by a central computer that has a
    detailed 3D map of the terrain and knows all the
    relevant laws of physics and strategies

15
16
Other approaches to AI
  • Learning through experience (Rodney Brooks Cog,
    Kismet)
  • Machines that experience the world in much the
    way human beings do
  • You can learn stuff on your own
  • Robotic insects example
  • Each leg containing a small circuit that tells it
    about basic movements
  • All local computation physically coupled through
    the body, with gait emerging spontaneously from
    circuits interaction

16
17
Areas of work in AI
  • Theory
  • Philosophy
  • Applications

18
Turing test
19
The Chinese room (John Searle)
20
Eliza (1966)
  • Conversation with ELIZA
  • Egt Hello. I am ELIZA. How can I help you?
  • Pgt I am feeling sad.
  • Egt I am sorry to hear you are sad.
  • Pgt I had some nightmares tonight.
  • Egt You say you had some nightmares tonight?
  • Pgt Yes, my dreams are worrying me.
  • Egt What does that dream suggest to you?
  • Pgt Thrill, scare.
  • Egt I am not sure I understand you fully.
  • Pgt My dreams annoy me.
  • Egt Do you dream often?
  • Pgt Yes, daily.

21
Lost in translation
  • English ? Russian (or Spanish)? English
  • The spirit is willing, but the flesh is weak ?
  • ? ??? ?????? ?????, ?? ????? ????? ?
  • ? The vodka is good, but the meat is rotten
  • (Actually Spirit is willingly ready, but flesh
    is weak or
  • The alcohol is arranged, but the meat is weak)

22
Autonomous robots
23
Personalization, recommendation
24
US District Court judge John E. Jones III
  • Proponents of intelligent design argued that
    their supposedly scientific alternative to
    evolutionary theory should be presented in
    biology classes.
  • An objective student can reasonably infer that
    the schools favored view is a religious one, and
    that the school is accordingly sponsoring a form
    of religion.

25
One book
  • What if I want to read just one book about
    artificial intelligence?
  • Darwin's Dangerous Idea by Daniel Dennett
  • In favor of materialistic Darwinism
  • Victims Noam Chomsky, Roger Penrose, John Searle
    and, specially, Stephen Jay Gould
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