CS101 Introduction to Computing Lecture 34 Intelligent Systems

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CS101 Introduction to ComputingLecture
34Intelligent Systems
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During the last lecture (Graphics Animation)

• We became familiar with the role that graphics
  and animations play in computing
• We discussed how graphics animation are
  displayed
• We also looked at several formats used for
  storing graphics and animation

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Computer Graphics

• Images created with the help of computers
• 2-D and 3-D (displayed on a 2-D screen but in
  such a way that they give an illusion of depth)
• Used for scientific research, artistic
  expression, or for industrial applications
• Graphics have made the computer interfaces more
  intuitive by removing the need to memorize
  commands

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Displaying Images

• Most all computer displays consist of a grid of
  tiny pixels arranged in a regular grid of rows
  and columns
• Images are displayed by assigning different
  colors to the pixels located in the desired
  portion of the computer display
• Lets discuss the pixel a bit more

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Pixel

• The smallest image forming element on a computer
  display
• The computer display is made up of a regular grid
  of these pixels
• The computer has the capability of assigning any
  color to any of the individual pixels on the
  display
• Lets now see how the computer displays a square

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Pixel Colors (1)

• The color of each pixel is generally represented
  in the form a triplet
• In a popular scheme the RGB scheme each part
  of the triplet represents the intensity of one of
  out of three primary colors red, green, blue
• Often, the intensity of each color is represented
  with a byte, resulting in 256x256x256 (16
  million) unique color combinations

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Color Mapping (1)

• Instead of letting each pixel assume one out of
  16 million possible colors, only a limited number
  of colors called the platelet are allowed
• For example, the platelet may be restricted to
  256 colors (requiring 1 byte/pixel instead of 3)

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Dithering

• In this scheme, pixels of alternating colors are
  used to simulate a color that is not present in
  the platelet
• For example, red and green pixels can be
  alternated to give the impression of bright
  yellow
• The quality of the displayed image is poorer

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Aliasing

• The computer screen consists of square-ish pixels
  arranged in a fixed grid
• At times, when a diagonal line is drawn on this
  grid, it looks more like a staircase, instead of
  a straight line
• This effect called aliasing can be managed by
  reducing the size of pixels

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Anti-Aliasing (1)

• Anti-aliasing is another technique used for
  managing the staircase effect
• Lets say that we need to draw a white
  straight-line such that it overlaps 60 with one
  pixel, and 40 with another initially, and near
  the end, 58, 41, and 1, respectively, with
  three pixels

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Vector or Object-Oriented Graphics

• Treats everything that is drawn as an object
• Objects retain their identity after they are
  drawn
• These objects can later be easily moved,
  stretched, duplicated, deleted, etc
• Are resolution independent
• Relatively small file size
• Examples swf, svg, wmf, ps

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Bit-Mapped or Raster Graphics

• Treats everything that is drawn as a bit-map
• If an object is drawn on top of another, it is
  difficult to move just one of them while leaving
  the other untouched
• Changing the resolution often requires
  considerable touch-up work
• Relatively large file size
• Examples gif, jpg, bmp

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3-D Graphics (1)

• Flat images enhanced to impart the illusion of
  depth
• We perceive the world and the objects in it in
  3-D - breadth, width, depth - although the images
  formed on the retinas of our eyes are 2-D
• The secret of 3-D perception stereo vision

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3-D Rendering

• The process of converting information about 3-D
  objects into a bit-map that can be displayed on a
  2-D computer display
• Computationally, very expensive!
• Steps
• Draw the wire-frame (skeleton, made with thin
  lines)
• Fill with colors, textures, patterns
• Add lighting effects (reflections, shadows)

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Animation

• Graphics in motion, e.g. cartoons
• Illusion of motion is created by showing the
  viewer a sequence of still images, rapidly
• Drawing those images - each slightly different
  from the previous one - used to be quite tedious
  work
• Computers have helped in cutting down some of the
  tediousness

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Tweening (2)

• This process of creating these in-between images
  from key images is called in-betweening (or
  tweening for short)
• The simplest algorithm for tweening calculates
  the position of a particular segment of an image
  by calculating the average of the positions of
  that same image segment belonging to adjacent key
  images

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Todays Goals(Intelligent Systems)

• To become familiar with the distinguishing
  features of intelligent systems with respect to
  other software systems
• To become able to appreciate the role of
  intelligent systems in scientific, business and
  consumer applications
• To look at several techniques for designing
  intelligent systems

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(Artificial) Intelligent Systems

• SW programs or SW/HW systems designed to perform
  complex tasks employing strategies that mimic
  some aspect of human thought
• One can debate endlessly about whether a certain
  system is intelligent or not
• But to my mind, the key criterion is evolution
  it is intelligent if it can learn (even if only a
  limited sense) and get better with time

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Not a Suitable Hammer for All Nails!

• if the nature of computations required in a task
  is not well understood
• or there are too many exceptions to the rules
• or known algorithms are too complex or
  inefficient
• then AI has the potential of offering an
  acceptable solution

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Selected Applications

• Games Chess, SimCity
• Image recognition
• Medical diagnosis
• Robots
• Business intelligence

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Sub-Categories of AI

• Expert systems
• Systems that, in some limited sense, can replace
  an expert
• Robotics
• Natural language processing
• Teaching computers to understand human language,
  spoken as well as written
• Computer vision

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Selected Techniques

• Artificial neural networks
• Genetic algorithms
• Rule-based systems
• Fuzzy logic

Many times, any one of them can solve the problem
at hand, but at others, only the right one will
do. Therefore, it is important to have some
appreciation of them all
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Neural Networks (1)

• Original inspiration was the human brain
  emphasis now on usefulness as a computational
  tool
• Many useful NN paradigms, but scope of today's
  discussion limited to the feed-forward network,
  the most popular paradigm

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Neural Networks (2)

• Feed-forward Network
• It is a layered structure consisting of a number
  of homogeneous and simple (but nonlinear)
  processing elements
• All processing is local to a processing element
  and is asynchronous
• During training the FN is forced to adjust its
  parameters so that its response to input data
  becomes closer to the desired response

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Genetic Algorithms (1)

• Based on Darwin's evolutionary principle of
  survival of the fittest
• GAs require the ability to recognize a good
  solution, but not how to get to that solution

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Genetic Algorithms (2)

• The procedure
• An initial set of random solutions is ranked in
  terms of ability to solve the problem at hand
• The best solutions are then crossbred and
  mutated to form a new set
• The ranking and formation of new solutions is
  continued until a good enough solution is found
  or

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Rulebased Systems (1)

• Based on the principles of the logical reasoning
  ability of humans
• Components of an RBS
• Rulebase
• Working memory
• Rule interpreter

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Rulebased Systems (2)

• The design process
• An RBS engineer interviews the expert to acquire
  the comprehensive set of heuristics that covers
  the situations that may occur in a given domain
• This set is then encoded in the form of IF-THEN
  structures to form the required RBS

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Fuzzy Logic (1)

• Based on the principles of the approximate
  reasoning faculty that humans use when faced with
  linguistic ambiguity
• The inputs and outputs of a fuzzy system are
  precise, only the reasoning is approximate

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Fuzzy Logic (2)

• Parts of the knowledgebase of a fuzzy system
• Fuzzy rules
• Fuzzy sets
• The output of a fuzzy system is computed by
  using
• The MIN-MAX technique for combining fuzzy rules
• The centroid method for defuzzification

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Now we know about a few techniquesLets now
consider the situation when we are given a
particular problem and asked to find an AI
solution to that problem.How do we determine
the right technique for that particular problem?
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Selection of an Appropriate AI Technique

• A given problem can be solved in several ways
• Even if 2 techniques produce solutions of a
  similar quality, matching the right technique to
  a problem can save on time resources
• Characteristics of an optimal technique
• The solution contains all of the required
  information
• The solution meets all other necessary criteria
• The solution uses all of the available (useful)
  knowledge

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How do we determine the suitability of a
particular AI technique for a given taskWe look
at the tasks requirements and then see which
technique fulfils those requirements more
completely the one which does, is the one we
use!Here are a few aspects of the task and the
techniques that we need to be aware off
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• Accuracy
• Explainability
• Response speed
• Scalability
• Compactness
• Flexibility
• Embedability
• Ease of use

• Learning curve
• Tolerance for complexity
• Tolerance for noise in data
• Tolerance for sparse data
• Independence from experts
• Development speed
• Computing ease

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ai
in action!
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Credit Card Issuance (1)

• Challenge. Increase the acceptance rate of card
  applicants who will turn out to be good credit
  risks
• Inputs. Applicant's personal and financial
  profiles
• Output. Estimated yearly loss if application is
  accepted

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Credit Card Issuance (2)

• Expert knowledge. Some rules of thumb are
  available
• Data. Profiles loss data available for 1
  million applicants
• Suitable technique?

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Determination of the Optimal Drug Dosage (1)

• Challenge. Warn the physician if she prescribes a
  dosage which is either too high or too low
• Inputs. Patient's medical record. Pharmaceutical
  drug dosage instructions
• Output. Warning along with reasons for the
  warning

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Determination of the Optimal Drug Dosage (2)

• Data. Medical records of thousands of patients.
  Drug dosage instructions on dozens of medicines
• Suitable technique?

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Prediction of Airline Cabin Crew's Preferences
(1)

• Challenge. Predict the future base/status
  preferences of the cabin crew of an airline. The
  predicted preferences will be used by the airline
  for forecasting its staffing and training
  requirements
• Inputs. Crew's personal profiles. Preference
  history. Other data.
• Output. Predicted preference card for a date one
  year in the future

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Prediction of Airline Cabin Crew's Preferences
(2)

• Expert knowledge. Some rules of thumb are
  available
• Data. Available for the last four years for 8000
  crew members
• Suitable technique?

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The Right Technique

• Selection of the right AI technique requires
  intimate knowledge about the problem as well as
  the techniques under consideration
• Real problems may require a combination of
  techniques (AI and/or nonAI) for an optimal
  solution

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A few more areas of AI applications
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Robotics

• Automatic machines that perform various tasks
  that were previously done by humans
• Example
• Pilot-less combat airplanes
• Land-mine hunters
• Autonomous vacuum-cleaners
• Components Body structure, actuators,
  power-source, sensors, controller (the AI-based
  part)

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Autonomous Web Agents (1)

• Also known as mobile agents, softbots
• Computer program that performs various actions
  continuously, autonomously on behalf of their
  principal!
• Key component of the Semantic Web of tomorrow

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Autonomous Web Agents (2)

• Multi-agent communities are being developed in
  which agents meet and represent the interests of
  their principals in negotiations or
  collaborations. Example
• Agents of a patient and a doctor get together to
  negotiate and select a mutually agreeable time,
  cost

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Decision Support Systems

• Interactive software designed to improve the
  decision-making capability of their users
• Utilize historical data, models to solve problems
• The do not make decisions - just assist in the
  process
• They provide decision-makers with information via
  easy to manage reports, what-if scenarios, and
  graphics

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The Future?

• Get ready to see robots playing a bigger role in
  our daily lives
• Robots will gradually move out of the industrial
  world and into our daily life, similar to the way
  computers did in the 80s
• Decision support systems will become a bigger
  part of the professional life of doctors,
  managers, marketers, etc
• Autonomous land, air, sea vehicles controlled
  from 1000s of miles away from the war zone

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Todays SummaryIntelligent Systems

• We looked at the distinguishing features of
  intelligent systems w.r.t. other software systems
• We looked at the role of intelligent systems in
  scientific, business, consumer and other
  applications
• We discussed several techniques for designing
  intelligent systems

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Next Lecture(Data Management)

• To become familiar with the issues and problems
  related to data-intensive computing
• To become able to appreciate data management
  concepts and their evolution over the years