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
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