1 / 18

Uninformed Search Strategies

Uninformed Search Strategies. Uninformed strategies use only information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search Iterative deepening search. Iterative Deepening Search. Iterative Deepening Search l = 0. Limit = 0.

collinse
Download Presentation

Uninformed Search Strategies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Uninformed Search Strategies • Uninformed strategies use only information available in the problem definition • Breadth-first search • Uniform-cost search • Depth-first search • Depth-limited search • Iterative deepening search

  2. Iterative Deepening Search

  3. Iterative Deepening Search l = 0 • Limit = 0

  4. Iterative Deepening Search l = 1 • Limit = 1

  5. Iterative Deepening Search l = 2 • Limit = 2

  6. Iterative Deepening Search l = 3 • Limit = 3

  7. Properties of Iterative Deepening Search • Complete?? Yes • Time?? (d+1)b0 + db1 + (d-1)b2 + … + bd = O(bd) • Space?? O(bd) • Optimal?? Yes, if step cost = 1Can be modified to explore uniform-cost treeNumerical comparison for b=10 and d=5, solution at far right:N(IDS) = 50 + 400 + 3,000 + 20,000 + 100,000 = 123,450N(BFS) = 10 + 100 + 1,000 + 10,000 + 100,000 + 999,990 = 1,111,100

  8. Summary of algorithms

  9. Activity • Consider a state space where the start state is number 1 and the successor function for state n returns two states, numbers 2n and 2n+1. • Suppose the goal state is 11. • List the order in which nodes will be visited in depth limited search with limit 4

  10. Solution • Depth Limited, l=4 • 1, 2, 4, 8, 16, 17, 9, 18, 19, 5, 10, 20, 21, 11

  11. Activity • Consider a state space where the start state is number 1 and the successor function for state n returns two states, numbers 2n and 2n+1. • Suppose the goal state is 11. • List the order in which nodes will be visited using iterative deepening.

  12. Solution • Iterative Deepening • 1, 1, 2, 3, 1, 2, 4, 5, 3, 6, 7, 1, 2, 4, 8, 9, 5, 10, 11

  13. Summary of algorithms

  14. Bidirectional Search

  15. Let’s Try Another • Breadth First • Depth First • Uniform Cost • Iterative Deepening

  16. PA #1 • Twiddle • Convert the 3x3 board from 9 "randomly placed" numbers to an ordered solution…

  17. PA#1 • You can play a version online at: http://www.chiark.greenend.org.uk/~sgtatham/puzzles/js/twiddle.html • http://www.chiark.greenend.org.uk/~sgtatham/puzzles/js/twiddle.html#3x3n2:9,5,7,2,3,1,8,4,6

  18. PA #1 • READ the specific requirements • Should use Python, Java, or get a language approved by me first. • Should print an optimal path, the number of nodes considered so far, and the number of nodes in memory at the end. • Should return the optimal path • Must follow naming conventions listed in assignment. (File named HW1, method named search)

More Related