Artificial Intelligence Introduction

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Artificial IntelligenceIntroduction

• Fall 2008
• professor Luigi Ceccaroni

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Instructors

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

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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

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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/

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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.

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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.

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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

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Topics

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

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Topics

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

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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

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Topics

• 5. Machine learning
• 5.1 Decision trees

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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.

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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.

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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)

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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

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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

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Areas of work in AI

• Theory
• Philosophy
• Applications

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Turing test
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The Chinese room (John Searle)
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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.

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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)

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Autonomous robots
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Personalization, recommendation
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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.

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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