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Jarrar.lecture notes.aai.2011s.ch3.uniformedsearch

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Dr. Mustafa Jarrar [email_address] University of Birzeit Chapter 3 Uni-Informed Search Advanced Artificial Intelligence (SCOM7341) Lecture Notes, Advanced Artificial Intelligence (SCOM7341) University of Birzeit 2 nd Semester, 2011
Example: Romania You are in Arad and want to go to Bucharest  How to design an intelligent agent to find the way between 2 cities?
Example: The 8-puzzle  How can we design an intelligent agent to solve the 8-puzzel?
Search as Problem-Solving Strategy ,[object Object],[object Object],[object Object]
Search as Problem-Solving Strategy ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Motivation ,[object Object],[object Object],[object Object]
Problem Formulation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Problem Formulation (The Romania Example) ,[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]
Problem Formulation (The 8- Puzzle Example) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Problem Formulation (Real-life Applications) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Car Navigation Routing in Computer networks Military operation planning Airline travel planning
Problem Formulation (Real-life Applications) ,[object Object], What is the state space for each of them? A set of places with links between them, which have been visited
Problem Formulation (Real-life Applications) ,[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]
Problem Formulation (Real-life Applications) ,[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]
Problem Formulation (Real-life Applications) ,[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]
Problem Formulation (Real-life Applications) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Searching for Solutions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Search Terminology ,[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]
Example: Graph Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
Traversing a Graph as Tree S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],2 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
Discussion Who can give examples of tree search strategies? Why a search strategy is better than another?
Example: Breadth First Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
Example: Greedy Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
Example: A* Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
General Tree Search ,[object Object],[object Object],[object Object],[object Object],[object Object]
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],[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation of Search Strategies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
1: Breadth-First Search
[object Object],Breadth-First Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Breadth-First Snapshot 1 Initial Visited Fringe Current Visible Goal 1 2 3 Fringe: [] + [2,3]
Breadth-First Snapshot 2 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 Fringe: [3] + [4,5]
Breadth-First Snapshot 3 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 Fringe: [4,5] + [6,7]
Breadth-First Snapshot 4 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 Fringe: [5,6,7] + [8,9]
Breadth-First Snapshot 5 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 Fringe: [6,7,8,9] + [10,11]
Breadth-First Snapshot 6 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 Fringe: [7,8,9,10,11] + [12,13]
Breadth-First Snapshot 7 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Fringe: [8,9.10,11,12,13] + [14,15]
Breadth-First Snapshot 8 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Fringe: [9,10,11,12,13,14,15] + [16,17]
Breadth-First Snapshot 9 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Fringe: [10,11,12,13,14,15,16,17] + [18,19]
Breadth-First Snapshot 10 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Fringe: [11,12,13,14,15,16,17,18,19] + [20,21]
Breadth-First Snapshot 11 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Fringe: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21] + [22,23]
Breadth-First Snapshot 12 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Fringe: [13,14,15,16,17,18,19,20,21] + [22,23] Note: The goal node is “visible” here, but we can not perform the goal test yet.
Breadth-First Snapshot 13 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Fringe: [14,15,16,17,18,19,20,21,22,23,24,25] + [26,27]
Breadth-First Snapshot 14 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Fringe: [15,16,17,18,19,20,21,22,23,24,25,26,27] + [28,29]
Breadth-First Snapshot 15 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29] + [30,31]
Breadth-First Snapshot 16 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 17 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [18,19,20,21,22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 18 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [19,20,21,22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 19 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [20,21,22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 20 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [21,22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 21 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [22,23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 22 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [23,24,25,26,27,28,29,30,31]
Breadth-First Snapshot 23 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [24,25,26,27,28,29,30,31]
Breadth-First Snapshot 24 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [25,26,27,28,29,30,31] Note: The goal test is positive for this node, and a solution is found in 24 steps.
Properties of Breadth-First Search (BFS) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],b Branching Factor d The depth of the goal
2- Uniform-Cost -First
[object Object],[object Object],[object Object],Uniform-Cost -First
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Uniform-Cost Search (UCS)
Properties of Uniform-cost Search (UCS) ,[object Object],[object Object],[object Object],[object Object],[object Object],b Branching Factor d Depth of the goal/tree
Breadth-First vs. Uniform-Cost ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
3- Depth-First Search
Depth-First Search ,[object Object],[object Object],[object Object],L M N O P G Q H J I K F E D B C A
Depth-First Search ,[object Object],[object Object],[object Object],[object Object],[object Object]
Recursive Depth-First Search ,[object Object],[object Object],[object Object],[object Object],print node and print c and
Properties of Depth-First Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Depth-First vs. Breadth-First ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
4- Depth-Limited Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],b branching factor l depth limit
5- Iterative Deepening Depth-First Search
[object Object],[object Object],[object Object],Iterative Deepening Depth-First Search
Iterative deepening search l =0
Iterative deepening search l =1
Iterative deepening search l =2
Iterative deepening search l =3
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Iterative Deepening Depth-First Search
Iterative Deepening Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Iterative Deepening Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Properties of Iterative Deepening Search ,[object Object],[object Object],[object Object],[object Object],b branching factor d Tree/goal depth
6- Bi-directional Search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],b branching factor d tree depth Time Complexity b d/2 Space Complexity b d/2 Completeness yes (b finite, breadth-first for both directions) Optimality yes (all step costs identical, breadth-first for both directions)
Summary ,[object Object],[object Object],Iterative deepening search uses only linear space and not much more time than other uninformed algorithms
[object Object],[object Object],[object Object],[object Object],Summary
Summary (When to use what) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Improving Search Methods ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Jarrar.lecture notes.aai.2011s.ch3.uniformedsearch

  • 1. Dr. Mustafa Jarrar [email_address] University of Birzeit Chapter 3 Uni-Informed Search Advanced Artificial Intelligence (SCOM7341) Lecture Notes, Advanced Artificial Intelligence (SCOM7341) University of Birzeit 2 nd Semester, 2011
  • 2. Example: Romania You are in Arad and want to go to Bucharest  How to design an intelligent agent to find the way between 2 cities?
  • 3. Example: The 8-puzzle  How can we design an intelligent agent to solve the 8-puzzel?
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20. Discussion Who can give examples of tree search strategies? Why a search strategy is better than another?
  • 21. Example: Breadth First Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
  • 22. Example: Greedy Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
  • 23. Example: A* Search S3 5 A4 D3 1 1 3 3 4 2 C2 D3 G0 G0 G0 E1 G0 1 1 3 3 4 2 C2 D3 G0 G0 E1 G0 1 3 B2 1 3 C2 D3 G0 G0 E1 G0 1 3 4 E1 G0 2 4 3 2 4 S3 A4 C2 D3 E1 B2 G0 1 1 1 3 1 3 3 4 5 1 2
  • 24.
  • 25.
  • 26.
  • 28.
  • 29. Breadth-First Snapshot 1 Initial Visited Fringe Current Visible Goal 1 2 3 Fringe: [] + [2,3]
  • 30. Breadth-First Snapshot 2 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 Fringe: [3] + [4,5]
  • 31. Breadth-First Snapshot 3 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 Fringe: [4,5] + [6,7]
  • 32. Breadth-First Snapshot 4 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 Fringe: [5,6,7] + [8,9]
  • 33. Breadth-First Snapshot 5 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 Fringe: [6,7,8,9] + [10,11]
  • 34. Breadth-First Snapshot 6 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 Fringe: [7,8,9,10,11] + [12,13]
  • 35. Breadth-First Snapshot 7 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Fringe: [8,9.10,11,12,13] + [14,15]
  • 36. Breadth-First Snapshot 8 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Fringe: [9,10,11,12,13,14,15] + [16,17]
  • 37. Breadth-First Snapshot 9 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Fringe: [10,11,12,13,14,15,16,17] + [18,19]
  • 38. Breadth-First Snapshot 10 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Fringe: [11,12,13,14,15,16,17,18,19] + [20,21]
  • 39. Breadth-First Snapshot 11 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Fringe: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21] + [22,23]
  • 40. Breadth-First Snapshot 12 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Fringe: [13,14,15,16,17,18,19,20,21] + [22,23] Note: The goal node is “visible” here, but we can not perform the goal test yet.
  • 41. Breadth-First Snapshot 13 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Fringe: [14,15,16,17,18,19,20,21,22,23,24,25] + [26,27]
  • 42. Breadth-First Snapshot 14 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Fringe: [15,16,17,18,19,20,21,22,23,24,25,26,27] + [28,29]
  • 43. Breadth-First Snapshot 15 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29] + [30,31]
  • 44. Breadth-First Snapshot 16 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]
  • 45. Breadth-First Snapshot 17 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [18,19,20,21,22,23,24,25,26,27,28,29,30,31]
  • 46. Breadth-First Snapshot 18 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [19,20,21,22,23,24,25,26,27,28,29,30,31]
  • 47. Breadth-First Snapshot 19 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [20,21,22,23,24,25,26,27,28,29,30,31]
  • 48. Breadth-First Snapshot 20 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [21,22,23,24,25,26,27,28,29,30,31]
  • 49. Breadth-First Snapshot 21 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [22,23,24,25,26,27,28,29,30,31]
  • 50. Breadth-First Snapshot 22 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [23,24,25,26,27,28,29,30,31]
  • 51. Breadth-First Snapshot 23 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [24,25,26,27,28,29,30,31]
  • 52. Breadth-First Snapshot 24 Initial Visited Fringe Current Visible Goal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Fringe: [25,26,27,28,29,30,31] Note: The goal test is positive for this node, and a solution is found in 24 steps.
  • 53.
  • 55.
  • 64.
  • 65.
  • 67.
  • 68.
  • 69.
  • 70.
  • 71.
  • 72.
  • 73. 5- Iterative Deepening Depth-First Search
  • 74.
  • 79.
  • 80.
  • 81.
  • 82.
  • 83.
  • 84.
  • 85.
  • 86.
  • 87.

Notes de l'éditeur

  1. anecdote, demonstration, example to informally introduce the topic evoke the participants’ interest and curiosity set the stage for the more formal introduction make students more comfortable