Lecture 15: Artificial intelligence: Hill climbing with 8 puzzle problem Weaknesses and solution
In this video we will talk about local search method and discuss one search algorithm hill climbing which belongs to local search method. We will also discuss the weaknesses of this algorithm with 8 puzzle problem then we will talk about the solution of these weaknesses.
Weaknesses of Algorithm:
Local maxima or local minima:
A state which is better than all of it’s neighbors but not better than some other state which is not directly connected to that state.
Plateau
A flat area of the search space in which all neighboring states have same values
Ridges
Creating a sequence of local maxima but all of them are not directly connected
Solution of hill climbing weaknesses
Random initialization of starting state
jump
#HillclimbingprobleminArtificialIntelligence #WeaknessesOfHillClimbing #SolutionOfhillClimbingWeaknesses #LocalMaximaLocalMinima #PlateauproblemInHillclimbing #RidgeProblemInHillclimbing
Видео Lecture 15: Artificial intelligence: Hill climbing with 8 puzzle problem Weaknesses and solution канала Muhammad Umar Farooq
Weaknesses of Algorithm:
Local maxima or local minima:
A state which is better than all of it’s neighbors but not better than some other state which is not directly connected to that state.
Plateau
A flat area of the search space in which all neighboring states have same values
Ridges
Creating a sequence of local maxima but all of them are not directly connected
Solution of hill climbing weaknesses
Random initialization of starting state
jump
#HillclimbingprobleminArtificialIntelligence #WeaknessesOfHillClimbing #SolutionOfhillClimbingWeaknesses #LocalMaximaLocalMinima #PlateauproblemInHillclimbing #RidgeProblemInHillclimbing
Видео Lecture 15: Artificial intelligence: Hill climbing with 8 puzzle problem Weaknesses and solution канала Muhammad Umar Farooq
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