1. CSE 4705 Artificial Intelligence
Jinbo Bi
Department of Computer Science & Engineering

2. Informed search strategies

3. Informed search Part I (classical search)
Informed = use problem-specific knowledge
Best-first search and its variants
A* - Optimal search using knowledge
Proof of optimality of A*
A* for maneuvering AI agents in games
Heuristic functions
Part II (beyond classical search, Chap 4)
Local search and optimization
Local search in continuous space
Hill climbing, local bean search, …

4. Informed search
Is Uniform cost search the best we can do?

5. A better idea

6. The straight-line distance from each city to Bucharest:
Start
Goal

7. A heuristic function

8. Breadth first for games, robots

9. An optimal informed search (A*)

10. Breadth first for a world with obstacles
Pink: start node;
Dark blue: goal
Breadth-first search expands many nodes

11. Informed search (A*) in that world

12. Greedy best-first search

13. Greedy best-first search example

14. Greedy best-first search example

15. Greedy best-first search example

16. Greedy best-first search example

17. Properties of greedy best-first search

18. Properties of greedy best-first search

19. Properties of greedy best-first search

20. A* search

21. Admissible heuristics

22. A* search example

23. A* search example

24. A* search example

25. A* search example

26. A* search example

27. A* search example

28. A* search example

29. Optimality of A* (intuitive)

30. Optimality of A* using tree search

31. Optimality of A* using tree search

32. Properties of A* search

33. Properties of A* search

34. Properties of A* search

35. Properties of A* search

36. A lemma: Consistency

37. Creating good heuristic functions
Chap 3.6

38. Heuristic functions

39. Heuristic functions

40. Admissible heuristics

41. Admissible heuristics8
=18

42. Relaxed problems

43. Defining heuristics: h(n)

44. Dominance

45. Iterative deepening A* and beyond

46. Iterative deepening A* and beyond

47. Informed search II When A* fails – hill climbing, simulated annealing
Genetic algorithms

48. Outline

49. Local search and optimization

50. Hill climbing

51. Hill climbing on a surface of states

52. Hill climbing search

53. Hill climbing search example4

54. Questions?