Searching Algorithms in AI

Various Searching Algorithm Used in AI
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Basic Search Algorithms used in AI.
Breadth-first search. Uniform cost search. Depth-first search. Iterative deepening depth-first search. Bidirectional Search.


  • Basic of Data Structure.


Searching is the universal technique of problem solving in AI. There are some single-player games such as tile games, Sudoku, crossword, etc. The search algorithms help you to search for a particular position in such games.

Single Agent Pathfinding Problems

The games such as 3X3 eight-tile, 4X4 fifteen-tile, and 5X5 twenty four tile puzzles are single-agent-path-finding challenges. They consist of a matrix of tiles with a blank tile. The player is required to arrange the tiles by sliding a tile either vertically or horizontally into a blank space with the aim of accomplishing some objective.

The other examples of single agent pathfinding problems are Travelling Salesman Problem, Rubik’s Cube, and Theorem Proving.

Search Terminology

· Problem Space − It is the environment in which the search takes place. (A set of states and set of operators to change those states)

· Problem Instance − It is Initial state + Goal state.

· Problem Space Graph − It represents problem state. States are shown by nodes and operators are shown by edges.

· Depth of a problem − Length of a shortest path or shortest sequence of operators from Initial State to goal state.

· Space Complexity − The maximum number of nodes that are stored in memory.

· Time Complexity − The maximum number of nodes that are created.

· Admissibility − A property of an algorithm to always find an optimal solution.

· Branching Factor − The average number of child nodes in the problem space graph.

· Depth − Length of the shortest path from initial state to goal state.

Brute-Force Search Strategies

They are most simple, as they do not need any domain-specific knowledge. They work fine with small number of possible states.

Requirements −

  • State description

  • A set of valid operators

  • Initial state

  • Goal state description

Who this course is for:

  • Engineering Student, Professional etc

Course content

1 section5 lectures1h 15m total length
  • 8 Puzzle Problem without Heuristic
  • 8 Puzzle Problem with Heuristic
  • Breadth First Search
  • A Star Algorithm
  • Gaming in AI


Assistant Professor at KKWIEER Nasik & Instructor
Smita Karpe (Shinde)
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  • 439 Students
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I, Mrs Smita Karpe BE in Electronics & ME in Embedded Systems is currently working as an Assistant Professor at one of the reputed and best engineering research institute in Nasik under Pune University known as KKWIEER i.e., K K Wagh Engineering and Research Institute.

I have vast experience in teaching the electronics engineering graduate student for over 13 years now. I have taught various subjects such as Basic of Electronics, Network Theorem, Signal Processing, Digital Electronics, DSP, Operating Systems, Analog & Digital Communication, AI etc.

Currently, I am teaching AI Artificial Intelligence. My Aim and purpose is to create course that will help the Engineering Students Learn Basic and Advance Concept of Electronics & Telecommunications Engineering.