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Heuristic Search
Prof. Neeraj Bhargava
Kapil Chauhan
Department of Computer Science
School of Engineering & Systems Sciences
MDS University, Ajmer
Content’s
 Introduction
 Techniques
 Statement
 8 Puzzel
 Advantages - Disadvantages
Heuristic Search
1) A Heuristic is a technique to solve a problem faster
than classic methods, or to find an approximate
solution when classic methods cannot.
2) This is a kind of a shortcut as we often trade one of
optimality, completeness, accuracy, or precision for
speed.
Heuristic Search Techniques in Artificial
Intelligence
Direct Heuristic Search Techniques in AI
Other names for these are Blind Search, Uninformed
Search, and Blind Control Strategy.
These aren’t always possible since they demand much
time or memory. They search the entire state space for a
solution and use an arbitrary ordering of operations.
Examples of these are Breadth First Search (BFS) and
Depth First Search (DFS).
Weak Heuristic Search Techniques in AI
 Other names for these are Informed Search, Heuristic
Search, and Heuristic Control Strategy.
 These are effective if applied correctly to the right types of
tasks and usually demand domain-specific information.
 We need this extra information to compute preference
among child nodes to explore and expand. Each node has a
heuristic function associated with it.
Statement for 8 Puzzel problem
 8 puzzel is Square track in which are placed 8square tiles .
 The remain 9th square are uncovered , each tile has a number on
it, tile that is adjutant to blank space can be adjust into that space.
 A game consist of starting position and a specified goal position ,
the goal is to transform the starting position into the goal position
by sliding the tiles around.
 For understand the heuristic we can take an example in which
heuristic function is used in Example i.e. 8 Puzzle
8 Puzzel problem
 The 8-puzzle problem is a puzzle invented and popularized by Noyes
Palmer Chapman in the 1870s.
 It is played on a 3-by-3 grid with 8 square blocks labeled 1 through 8
and a blank square.
 Our goal is to rearrange the blocks so that they are in order. You are
permitted to slide blocks horizontally or vertically into the blank square.
Solution
ADVANTAGES DISADVANTAGES
 It can provide some quick and
relatively inexpensive feedback to
designers.
 You can obtain feedback early in the
design process.
 Assigning the correct heuristic can
help suggest the best corrective
measures to designers.
 You can use it together with other
usability testing methodologies.
 You can conduct usability testing to
further examine potential issues.
 It requires knowledge and
experience to apply the heuristics
effectively.
 Trained usability experts are
sometimes hard to find and can be
expensive.
 You should use multiple experts and
aggregate their results.
 The evaluation may identify more
minor issues and fewer major issues.
Assignment
 Explain Heuristic search in deep learning problem
with suitable example.

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Herusitic search

  • 1. Heuristic Search Prof. Neeraj Bhargava Kapil Chauhan Department of Computer Science School of Engineering & Systems Sciences MDS University, Ajmer
  • 2. Content’s  Introduction  Techniques  Statement  8 Puzzel  Advantages - Disadvantages
  • 3. Heuristic Search 1) A Heuristic is a technique to solve a problem faster than classic methods, or to find an approximate solution when classic methods cannot. 2) This is a kind of a shortcut as we often trade one of optimality, completeness, accuracy, or precision for speed.
  • 4. Heuristic Search Techniques in Artificial Intelligence
  • 5. Direct Heuristic Search Techniques in AI Other names for these are Blind Search, Uninformed Search, and Blind Control Strategy. These aren’t always possible since they demand much time or memory. They search the entire state space for a solution and use an arbitrary ordering of operations. Examples of these are Breadth First Search (BFS) and Depth First Search (DFS).
  • 6. Weak Heuristic Search Techniques in AI  Other names for these are Informed Search, Heuristic Search, and Heuristic Control Strategy.  These are effective if applied correctly to the right types of tasks and usually demand domain-specific information.  We need this extra information to compute preference among child nodes to explore and expand. Each node has a heuristic function associated with it.
  • 7. Statement for 8 Puzzel problem  8 puzzel is Square track in which are placed 8square tiles .  The remain 9th square are uncovered , each tile has a number on it, tile that is adjutant to blank space can be adjust into that space.  A game consist of starting position and a specified goal position , the goal is to transform the starting position into the goal position by sliding the tiles around.  For understand the heuristic we can take an example in which heuristic function is used in Example i.e. 8 Puzzle
  • 8. 8 Puzzel problem  The 8-puzzle problem is a puzzle invented and popularized by Noyes Palmer Chapman in the 1870s.  It is played on a 3-by-3 grid with 8 square blocks labeled 1 through 8 and a blank square.  Our goal is to rearrange the blocks so that they are in order. You are permitted to slide blocks horizontally or vertically into the blank square.
  • 10. ADVANTAGES DISADVANTAGES  It can provide some quick and relatively inexpensive feedback to designers.  You can obtain feedback early in the design process.  Assigning the correct heuristic can help suggest the best corrective measures to designers.  You can use it together with other usability testing methodologies.  You can conduct usability testing to further examine potential issues.  It requires knowledge and experience to apply the heuristics effectively.  Trained usability experts are sometimes hard to find and can be expensive.  You should use multiple experts and aggregate their results.  The evaluation may identify more minor issues and fewer major issues.
  • 11. Assignment  Explain Heuristic search in deep learning problem with suitable example.