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Chapter 4 Informed Search and Exploration

Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Informed search strategies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Greedy best-first search ,[object Object],[object Object]

Greedy best-first search example

Properties of Greedy best-first search ,[object Object],[object Object],[object Object],[object Object],No No – can get stuck in loops, e.g., Iasi –> Neamt – > Iasi – > Neamt Yes – complete in finite states with repeated-state checking , but a good heuristic function can give dramatic improvement – keeps all nodes in memory

A* search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

: Straight line distance heuristic

Optimality of A* ,[object Object],[object Object],[object Object],[object Object],[object Object]

Properties of A* ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Memory-bounded heuristic search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Memory-bounded heuristic search (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

(Admissible) Heuristic Functions h 1 ? h 2 ? = the number of misplaced tiles = total Manhattan (city block) distance = 7 tiles are out of position = 4+0+3+3+1+0+2+1 = 14

Effect of heuristic accuracy ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Inventing admissible heuristic functions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Local search algorithms and optimization ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Local search – state space landscape ,[object Object],global minimum heuristic cost function ,[object Object],[object Object]

[object Object],[object Object],[object Object],[object Object],Hill-climbing search

[object Object],[object Object],[object Object],Hill-climbing search - example best moves reduce h = 17 to h = 12 local minimum with h = 1

Hill-climbing search – greedy local search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Hill-climbing search – improvement ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Simulated annealing search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Simulated annealing search - Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object]

Local beam search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Genetic algorithms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Genetic algorithms (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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