Artificial Intelligence Lecture 2:Knowledge Representation I

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Artificial IntelligenceLecture 2Knowledge
Representation I

• Faculty of Mathematical Sciences
• 4th
• 5th IT
• Elmuntasir Abdallah Hag Eltom

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Lecture ObjectivesPart I Chapter 2

• Look at some of the arguments against strong AI
  (the belief that a computer is capable of having
  mental states).
• Look at the prevalence of Artificial Intelligence
  today and explain why it has become such a vital
  area of study.
• Look at the extent to which the Artificial
  Intelligence community has been successful so far
  in achieving the goals that were believed to be
  possible decades ago. In particular, we will look
  at whether the computer HAL in the science
  fiction film 2001 A Space Odyssey is a
  possibility with todays technologies.

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Lecture Objectives Part II Chapter 3

• Discuss representations. The reason for this is
  that in order for a computer to solve a problem
  that relates to the real world, it first needs
  some way to represent the real world internally.
  In dealing with that internal representation, the
  computer is then able to solve problems.
• Introduce a number of representations, such as
  semantic nets, goal trees, and search trees.
• Explains why these representations provide such a
  powerful way to solve a wide range of problems.
• Introduce frames and the way in which inheritance
  can be used to provide a powerful
  representational system.

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The limits of my language mean the limits of my
world.-Ludwig Wittgenstein.The Chinese Room

• The American philosopher John Searle has argued
  strongly against the proponents of strong AI who
  believe that a computer that behaves sufficiently
  intelligently could in fact be intelligent and
  have consciousness, or mental states, in much the
  same way that a human does.
• One example of this is that it is possible using
  data structures called scripts to produce a
  system that can be given a story (for example, a
  story about a man having dinner in a restaurant)
  and then answer questions (some of which involve
  a degree of subtlety) about the story. Proponents
  of strong AI would claim that systems that can
  extend this ability to deal with arbitrary
  stories and other problems would be intelligent.

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The limits of my language mean the limits of my
world.-Ludwig Wittgenstein.The Chinese Room

• Searles Chinese Room experiment was based on
  this idea and is described as follows
• An English-speaking human is placed inside a
  room. This human does not speak any language
  other than English and in particular has no
  ability to read, speak, or understand Chinese.
• Inside the room with the human are a set of
  cards, upon which are printed Chinese symbols,
  and a set of instructions that are written in
  English.
• A story, in Chinese, is fed into the room through
  a slot, along with a set of questions about the
  story.

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The limits of my language mean the limits of my
world.-Ludwig Wittgenstein.The Chinese Room

• By following the instructions that he has, the
  human is able to construct answers to the
  questions from the cards with Chinese symbols and
  pass them back out through the slot to the
  questioner.
• If the system were set up properly, the answers
  to the questions would be sufficient that the
  questioner would believe that the room (or the
  person inside the room) truly understood the
  story, the questions, and the answers it gave.

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The limits of my language mean the limits of my
world.-Ludwig Wittgenstein.The Chinese Room

• Searles argument is now a simple one.
• The man in the room does not understand Chinese.
  The pieces of card do not understand Chinese. The
  room itself does not understand Chinese, and yet
  the system as a whole is able to exhibit
  properties that lead an observer to believe that
  the system (or some part of it) does understand
  Chinese
• In other words, running a computer program that
  behaves in an intelligent way does not
  necessarily produce understanding, consciousness,
  or real intelligence.

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The limits of my language mean the limits of my
world.-Ludwig Wittgenstein.The Chinese Room

• This argument clearly contrasts with Turings
  view that a computer system that could fool a
  human into thinking it was human too would
  actually be intelligent.
• One response to Searles Chinese Room argument,
  the Systems Reply, claims that although the human
  in the room does not understand Chinese, the room
  itself does. In other words, the combination of
  the room, the human, the cards with Chinese
  characters, and the instructions form a system
  that in some sense is capable of understanding
  Chinese stories. There have been a great number
  of other objections to Searles argument, and the
  debate continues.
• Find more other arguments like the Chinese Room

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Human Brain as a Computer

• The Halting Problem and G?odels incompleteness
  theorem tell us that there are some functions
  that a computer cannot be programmed to compute,
  and as a result, it would seem to be impossible
  to program a computer to perform all the
  computations needed for real consciousness. This
  is a difficult argument, and one potential
  response to it is to claim that the human brain
  is in fact a computer, and that although it must
  also be limited by the Halting Problem, it is
  still capable of intelligence.

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Human Brain as a Computer

• Neural Networks is based on the claim that the
  human brain is a computer.
• By combining the processing power of individual
  neurons, we are able to produce artificial neural
  networks that are capable of solving extremely
  complex problems, such as recognizing faces.
• Proponents of strong AI might argue that such
  successes are steps along the way to producing an
  electronic human being.
• Objectors would point out that this is simply a
  way to solve one small set of problemsnot only
  does it not solve the whole range of problems
  that humans are capable of, but it also does not
  in any way exhibit anything approaching
  consciousness.

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HALFantasy or Reality?

• In the film 2001 A Space Odyssey. One of the
  main characters in the film is HAL, a
  Heuristically programmed ALgorithmic computer. In
  the film, HAL behaves, speaks, and interacts with
  humans in much the same way that a human would,
  In fact, this humanity is taken to extremes by
  the fact that HAL eventually goes mad.
• In the film, HAL played chess, worked out what
  people were saying by reading their lips, and
  engaged in conversation with other humans.
• How many of these tasks are computers capable of
  today? Games, Natural Language Processing,
  Machine Vision
• Finally, the likelihood of a computer becoming
  insane is a rather remote one, although it is of
  course possible that a malfunction of some kind
  could cause a computer to exhibit properties not
  unlike insanity!

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Fantasy or Reality?

• Artificial Intelligence has been widely
  represented in other films. The Stephen Spielberg
  film AIArtificial Intelligence is a good
  example. In this film, a couple buy a robotic boy
  to replace their lost son. The audiences
  sympathies are for the boy who feels emotions and
  is clearly as intelligent (if not more so) as a
  human being. This is strong AI, and while it may
  be the ultimate goal of some Artificial
  Intelligence research, even the most optimistic
  proponents of strong AI would agree that it is
  not likely to be achieved in the next century

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AI in the 21st Century

• Artificial Intelligence is all around us.
• Fuzzy logic, for example, is widely used in
  washing machines, cars, and elevator control
  mechanisms. (Note that no one would claim that as
  a result those machines were intelligent, or
  anything like it! They are simply using
  techniques that enable them to behave in a more
  intelligent way than a simpler control mechanism
  would allow.)

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AI in the 21st Century

• Intelligent agents, are widely used. For example,
  there are agents that help us to solve problems
  while using our computers and agents that
  traverse the Internet, helping us to find
  documents that might be of interest. The physical
  embodiment of agents, robots, are also becoming
  more widely used. Robots are used to explore the
  oceans and other worlds, being able to travel in
  environments inhospitable to humans. It is still
  not the case, as was once predicted, that robots
  are widely used by households, for example, to
  carry shopping items or to play with children,
  although the AIBO robotic dog produced by Sony
  and other similar toys are a step in this
  direction.

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Part I Chapter 2 Summary

• The Chinese Room argument is a thought
  experiment designed by
• John Searle, which is designed to refute strong
  AI.
• The computer HAL, as described in the film
  2001 A Space Odyssey,
• is not strictly possible using todays
  technology, but many of its
• capabilities are not entirely unrealistic today.
• The computer program, Deep Blue, beat world
  chess champion
• Garry Kasparov in a six-game chess match in 1997.
  This feat has
• not been repeated, and it does not yet represent
  the end of human
• supremacy at this game.
• Artificial Intelligence is all around us and is
  widely used in industry,
• computer games, cars, and other devices, as well
  as being a
• valuable tool used in many computer software
  programs.

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Part II Knowledge Representation

• If, for a given problem, we have a means of
  checking a proposed solution, then we can solve
  the problem by testing all possible answers. But
  this always takes much too long to be of
  practical interest. Any device that can reduce
  this search may be of value.
• -Marvin Minsky, Steps Toward Artificial
  Intelligence

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Part II Knowledge Representation

• The way in which the computer represents a
  problem, the variables it uses, and the operators
  it applies to those variables can make the
  difference between an efficient algorithm and an
  algorithm that doesnt work at all. This is true
  of all Artificial Intelligence problems, and as
  we see in the following, it is vital for search.
• The example Contact lens problem

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Contact lens problem

• Imagine that you are looking for a contact lens
  that you dropped on a football field. You will
  probably use some knowledge about where you were
  on the field to help you look for it. If you
  spent time in only half of the field, you do not
  need to waste time looking in the other half.

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Contact lens problem

• Now let us suppose that you are having a computer
  search the field for the contact lens, and let us
  further suppose that the computer has access to
  an omniscient oracle that will answer questions
  about the field and can accurately identify
  whether the contact lens is in a particular spot.
• Now we must choose a representation for the
  computer to use so that it can formulate the
  correct questions to ask.

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Contact lens problem Representation 1

• One representation might be to have the computer
  divide the field into four equal squares and ask
  the oracle for each square, Is the lens in this
  square?.
• This will identify the location on the field of
  the lens but will not really be very helpful to
  you because you will still have a large area to
  search once you find which quarter of the field
  the lens is in.

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Contact lens problem Representation 2

• Another representation might be for the computer
  to have a grid containing a representation of
  every atom contained in the field. For each atom,
  the computer could ask its oracle, Is the lens
  in contact with this atom?
• This would give a very accurate answer indeed,
  but would be an extremely inefficient way of
  finding the lens. Even an extremely powerful
  computer would take a very long time indeed to
  locate the lens.

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Contact lens problem Representation 3

• Perhaps a better representation would be to
  divide the field up into a grid where each square
  is one foot by one foot and to eliminate all the
  squares from the grid that you know are nowhere
  near where you were when you lost the lens. This
  representation would be much more helpful.

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• In fact, the representations we have described
  for the contact lens problem are all really the
  same representation, but at different levels of
  granularity.
• The more difficult problem is to determine the
  data structure that will be used to represent the
  problem we are exploring.
• There are a wide range of representations used in
  Artificial Intelligence.

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• When applying Artificial Intelligence to search
  problems, a useful, efficient, and meaningful
  representation is essential. In other words, the
  representation should be such that the computer
  does not waste too much time on pointless
  computations, it should be such that the
  representation really does relate to the problem
  that is being solved, and it should provide a
  means by which the computer can actually solve
  the problem.

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Semantic Nets

• A semantic net is a graph consisting of nodes
  that are connected by edges.
• The nodes represent objects.
• The links between nodes represent relationships
  between those objects.
• The links are usually labeled to indicate the
  nature of the relationship

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Semantic Nets
Instances
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Semantic Nets

• The links are arrows, meaning that they have a
  direction. In this way. It may be that Fang does
  chase Fido as well, but this information is not
  presented in this diagram.
• Semantic nets do have limitations, such as the
  inability to represent negations Fido is not a
  cat., this kind of fact can be expressed easily
  in first-order predicate logic and can also be
  managed by rule-based systems.