Robotics Versus Artificial Intelligence. Search

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Robotics VersusArtificial Intelligence. Search
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Search

• All AI is search
• Game theory
• Problem spaces
• Every problem is a feature space of all possible
  (successful or unsuccessful) solutions.
• The trick is to find an efficient search strategy
  in this space.

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Example of an Intelligent Action

• Getting ready to come to class
• Describe so a machine could do it
• search among alternatives (car or bus)
• represent the knowledge

This requires a lot of knowledge!
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Search

• Example Four three-letter crossword puzzle
• Search problem is find correct puzzle
• Approaches
• word fill
• take word,
• put it to space,
• if contradiction, backtrack
• space fill
• take vertical or horizontal space
• select a word with this length
• put it into space,
• if contradiction, backtrack
• Many other strategies homework, find space and
  operators in it, discuss backtracking strategy

Cat dog cam may mom sit mit
C A M
A O
T O M
This is a mapping problem belongs to CSP
family of problems
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Blind Search

• Search depends only on nodes position in the
  search tree
• Two basic blind searches
• depth-first
• breadth-first

• Problem define depth-first search for the above
  problem
• Problem define breadth-first algorithm for the
  above problem.
• Repeat both for each of the approaches outlined
  above in the previous slide.

Called also search strategies
General problem solving method
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Depth-First Search Pseudo-Code

• 1. Set L to list of initial nodes
• 2. n head(L), Empty(L) gt fail
• 3. If ngoal, stop, return it and return the path
  leading to it
• 4. pop(L), push(L) all ns children,
• 5. go to step 2

Depth First is based on a stack, L
Head car in LISP
empty null in LISP
push(L)
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Breadth-First Search

• 1. Set L to list of initial nodes
• 2. nhead(L), Empty(L)gt fail
• 3. If ngoal then stop and return it and path
• 4. Dequeue(L), Enqueue(L) all ns children
• 5. Go to step 2

Depth First is based on a queue, L
Means, remove from queue
Means, add to queue
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Heuristic Search

• Meta-level reasoning
• heuristic function aids in selecting which part
  of search tree to expand
• trade-off between time to compute heuristic
  function and to expand the tree

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Other Issues

• Backtracking
• chronological backtracking as in Prolog
• dependency-directed backtracking
• Search direction
• forward (toward goal)
• backward (from goal)
• and math proving problems
• Bi-directional
• and building tunnel story

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Search Examples I

• Game playing
• chess
• backgammon
• Finding path to goal
• Missionaries and cannibals
• Towers of Hanoi
• Sliding Tile games (15, 8) , puzzles

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Search Examples II

• finding a goal
• cryptoarithmetic
• n-queens
• mutilated checkboard or tough nut of McCarthy
  problem.

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Example Applications of search

• Expert Systems
• Natural Language Processing
• Vision
• Robotics
• Robot in labyrinth
• Robot-human interaction hands movements
• Natural language communication
• Imitation of human movement
• Robot vision recognizing boxes in space
• Speech processing.

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Search Game Theory
tic-tac-toe,
9!1 362,880
Robot interaction with humans, other robots and
environment can be described in terms of a game
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Application Game playing programs

• Programs that
• take advantage of the computer's ability to
  examine a large number of possible moves in a
  short period of time and
• logically assess their probable success or
  failure
• have been already developed
• They were used for game playing in
• tic-tac-toe,
• checkers,
• chess,
• and the Oriental game called Go.

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Recent Trends in Artificial Intelligence

• Intelligent agents
• Experimental AI software designed to sift through
  masses of information made available on the
  evolving Information Superhighway of cyberspace
  to suggest topics of interest or importance for
  an individual.
• Artificial life
• A field of AI research that studies the adaptive
  control systems of insects and other ecological
  systems and reproduces them in robotic
  insectoids.
• More recently researchers have been working on
  robots with the intelligence of a two-year-old
  child.
• Intelligent Agents and Artificial Life are now
  part of robotics

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Typical tasks in mobile robotics, as related to
your projects

• Search give an example of search problem that
  can be solved using Lisp and that has not been
  presented so far in the class
• Robot in free space with chairs and people
• Robot in maze
• Robots arm in reaching in space with obstacles
• Blind and informed search for your problem, give
  an example of blind search and informed search.
  Create a powerful heuristic to solve it.
• Games
• examples of games include tic-tac-toe, checkers,
  chess, go, othello, etc.
• What kind of game can be a good choice for our
  robot-guard in the FAB building environment?
• Robot plays scissors-paper-rock game with a human
• What other games can be adapted to our mobile
  robots with hands and heads. These games must be
  short and visual. Not chess or checkers.

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Typical tasks in mobile robotics, as related to
your projects

• Expert system for robot guiding PSU visitors to
  offices of ECE faculty
• what kind of expert knowledge is needed for our
  walking guard, in addition to knowledge about the
  FAB building geometry, distances from room to
  room?
• who sits in which office?
• structure of ECE department and its people, etc.?
• How is this knowledge stored and accessed?

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Possible Programming Problems

• 1. Mouse in Labyrinth design an algorithm that
  will be able to go out of every labyrinth.
  Discuss the program strategy versus some
  knowledge of the labyrinth geometry. What kind of
  concepts introduced so far in the class may be
  useful? Discuss using depth-first, breadth-first
  search and other search strategies.
• 2. Obstacle Avoiding robot design a program
  that will simulate a turtle avoiding obstacles.
  In contrast to your homework 2, however, the
  turtle can recognize type of the obstacle and
  select the best strategy. The best strategy is
  not necessarily to follow the outline of the
  obstacle, but to go straight between two
  obstacles, sometimes closer to one of them. This
  is a useful sub-problem of avoiding stationary
  obstacles in the corridor or room for our robot.
• A program like this was written in class. Read
  about Voronoi diagrams and their uses in
  robotics.
• Think how these diagrams can be improved if you
  have more knowledge of obstacles.