The document discusses uninformed search techniques. It provides examples of representing problems as states and operators that transform states. This includes problems like the water jug problem, 8-puzzle, and 8-queens. It then describes common uninformed search algorithms like breadth-first search, depth-first search, iterative deepening, and uniform cost search. It analyzes the properties of these algorithms like completeness, time complexity, space complexity, and optimality.

5. Problem solving by search Represent the problem as STATES and OPERATORS that transform one state into another state. A solution to the problem is an OPERATOR SEQUENCE that transforms the INITIAL STATE into a GOAL STATE . Finding the sequence requires SEARCHING the STATE SPACE by GENERATING the paths connecting the two.

7. Example: Measuring problem! A c B A B C 0 0 0 3 0 0 3 0 3 0 0 6 3 0 6 0 3 6 3 3 6 1 5 6 0 5 7 3 l 5 l 9 l

21. Tree for water jug problem (0,0,0) (0,3,0) (4,0, 0) (0,0,0) (1,3,0) (4,3,0) (0,0,0) (3,0,0) (0,3,0) (1,0,0) (4,0,0) (4,3,0)     (4,3,0)

35. Breath-first search Expand the tree in successive layers, uniformly looking at all nodes at level n before progressing to level n+1 function Breath-First-Search( problem ) returns solution nodes := Make-Queue(Make-Node(Initial-State( problem )) loop do if nodes is empty then return failure node := Remove-Front (nodes) if Goal-Test[ problem ] applied to State( node ) succeeds then return node new-nodes := Expand (node, O perators [problem])) nodes := Insert-At-End-of-Queue (new-nodes) end

36. Another Breath-first search S A D B D A E C E E B B F D F B F C E A C G G C G F 14 19 19 17 17 15 15 13 G 25 11

39. Depth-first

47. Depth first search Dive into the search tree as far as you can, backing up only when there is no way to proceed function Depth-First-Search( problem ) returns solution nodes := Make-Queue(Make-Node(Initial-State( problem )) loop do if nodes is empty then return failure node := Remove-Front (nodes) if Goal-Test[ problem ] applied to State( node ) succeeds then return node new-nodes := Expand (node, O perarors [problem])) nodes := Insert-At-Front-of-Queue (new-nodes) end

48. Depth-first search S A D B D A E C E E B B F D F B F C E A C G G C G F 14 19 19 17 17 15 15 13 G 25 11