Informed Search (A , Heuristics Admissibility) Definition: Informed search is a search algorithm that incorporates additional information or knowledge a...
Informed Search (A, Heuristics Admissibility)*
Definition:
Informed search is a search algorithm that incorporates additional information or knowledge about the problem being solved into the search process. This knowledge can be represented by heuristics, which are rules or guidelines that guide the search towards promising regions of the search space.
Example:
Imagine a chess game where you know the location of all the pieces on the board. In an informed search algorithm using heuristics, you could prioritize moves that are likely to lead the opponent's pieces to dangerous positions.
How it works:
Informed search algorithms maintain a data structure called a knowledge base that stores additional information. This knowledge base can include:
Heuristics: Rules or guidelines used to prioritize moves.
Costs: Measures of how far a move is from the goal.
Probabilities: Estimates of the probability of finding the goal from a given state.
Key Concepts:
Heuristics: Rules or guidelines that guide the search towards promising regions.
Knowledge base: A data structure that stores additional information used by the algorithm.
Prioritization: Making decisions based on the most promising information.
Search space: The set of all possible states that can be reached from the starting state.
Advantages:
Improved performance by utilizing knowledge about the problem.
Can handle problems that are difficult or impossible to solve with traditional search algorithms.
Disadvantages:
Increased computational complexity.
Can be sensitive to the quality of the knowledge base