- Aug 17 12:20 AMLook at the Java code for aima.examples.TestSearch.java. This test is

solving two problems. The TwoThreeState problem is to get to a state

consisting of a number that is evenly divisible by 23, starting at zero. The

two operators are to add 2 or add 3. Each search prints out the path to the

goal in reverse order. So a depth-first search achieves the goal with a path

of length 23, each time applying the add2 operator. Breadth First Search

takes only 8 steps, most of them add3. A* Search takes 11 steps. Why more?

Because the costs of the operators is 2 for add2 and 4 for add3, so the

optimal solution perfers add2.

The other problem is missionaries and cannibals. The state (3,3,1) means 3

missionaries, 3 cannibals and 1 boat on the left side of the river; the goal

is to get them all to the other bank. All the search techniques shown solve

the problem in 11 steps.

-Peter

----- Original Message -----

From: "dpbatagoda" <dharshana@...>

To: <aima-talk@yahoogroups.com>

Sent: Friday, August 16, 2002 9:04 PM

Subject: [aima-talk] Pls Help Me

> Dear everybody,

> I am an instructure at Sri Lanka Institute of Information Technology.

> I really apreciate if you can explain this output from

> aima.examples.TestSearch?

>

>

>

> Trivial search space based on adding 2 or 3

> DFS:

> State: (46) Depth: 23 Cost: 46.0 by applying add2

> State: (44) Depth: 22 Cost: 44.0 by applying add2

> State: (42) Depth: 21 Cost: 42.0 by applying add2

> State: (40) Depth: 20 Cost: 40.0 by applying add2

> State: (38) Depth: 19 Cost: 38.0 by applying add2

> State: (36) Depth: 18 Cost: 36.0 by applying add2

> State: (34) Depth: 17 Cost: 34.0 by applying add2

> State: (32) Depth: 16 Cost: 32.0 by applying add2

> State: (30) Depth: 15 Cost: 30.0 by applying add2

> State: (28) Depth: 14 Cost: 28.0 by applying add2

> State: (26) Depth: 13 Cost: 26.0 by applying add2

> State: (24) Depth: 12 Cost: 24.0 by applying add2

> State: (22) Depth: 11 Cost: 22.0 by applying add2

> State: (20) Depth: 10 Cost: 20.0 by applying add2

> State: (18) Depth: 9 Cost: 18.0 by applying add2

> State: (16) Depth: 8 Cost: 16.0 by applying add2

> State: (14) Depth: 7 Cost: 14.0 by applying add2

> State: (12) Depth: 6 Cost: 12.0 by applying add2

> State: (10) Depth: 5 Cost: 10.0 by applying add2

> State: (8) Depth: 4 Cost: 8.0 by applying add2

> State: (6) Depth: 3 Cost: 6.0 by applying add2

> State: (4) Depth: 2 Cost: 4.0 by applying add2

> State: (2) Depth: 1 Cost: 2.0 by applying add2

> Starting at state: (0)

>

> Depth Bounded (depth 7):

> No solution

>

> BFS:

> State: (23) Depth: 8 Cost: 30.0 by applying add2

> State: (21) Depth: 7 Cost: 28.0 by applying add3

> State: (18) Depth: 6 Cost: 24.0 by applying add3

> State: (15) Depth: 5 Cost: 20.0 by applying add3

> State: (12) Depth: 4 Cost: 16.0 by applying add3

> State: (9) Depth: 3 Cost: 12.0 by applying add3

> State: (6) Depth: 2 Cost: 8.0 by applying add3

> State: (3) Depth: 1 Cost: 4.0 by applying add3

> Starting at state: (0)

>

>

> Uniform cost:

> State: (23) Depth: 11 Cost: 24.0 by applying add3

> State: (20) Depth: 10 Cost: 20.0 by applying add2

> State: (18) Depth: 9 Cost: 18.0 by applying add2

> State: (16) Depth: 8 Cost: 16.0 by applying add2

> State: (14) Depth: 7 Cost: 14.0 by applying add2

> State: (12) Depth: 6 Cost: 12.0 by applying add2

> State: (10) Depth: 5 Cost: 10.0 by applying add2

> State: (8) Depth: 4 Cost: 8.0 by applying add2

> State: (6) Depth: 3 Cost: 6.0 by applying add2

> State: (4) Depth: 2 Cost: 4.0 by applying add2

> State: (2) Depth: 1 Cost: 2.0 by applying add2

> Starting at state: (0)

>

> Iterated Deepening Search:

> State: (23) Depth: 8 Cost: 30.0 by applying add3

> State: (20) Depth: 7 Cost: 26.0 by applying add3

> State: (17) Depth: 6 Cost: 22.0 by applying add3

> State: (14) Depth: 5 Cost: 18.0 by applying add3

> State: (11) Depth: 4 Cost: 14.0 by applying add3

> State: (8) Depth: 3 Cost: 10.0 by applying add3

> State: (5) Depth: 2 Cost: 6.0 by applying add3

> State: (2) Depth: 1 Cost: 2.0 by applying add2

> Starting at state: (0)

>

> A* Search:

> State: (23) Depth: 11 Cost: 24.0 by applying add3

> State: (20) Depth: 10 Cost: 20.0 by applying add2

> State: (18) Depth: 9 Cost: 18.0 by applying add2

> State: (16) Depth: 8 Cost: 16.0 by applying add2

> State: (14) Depth: 7 Cost: 14.0 by applying add2

> State: (12) Depth: 6 Cost: 12.0 by applying add2

> State: (10) Depth: 5 Cost: 10.0 by applying add2

> State: (8) Depth: 4 Cost: 8.0 by applying add2

> State: (6) Depth: 3 Cost: 6.0 by applying add2

> State: (4) Depth: 2 Cost: 4.0 by applying add2

> State: (2) Depth: 1 Cost: 2.0 by applying add2

> Starting at state: (0)

>

> Greedy Search:

> State: (23) Depth: 8 Cost: 30.0 by applying add2

> State: (21) Depth: 7 Cost: 28.0 by applying add3

> State: (18) Depth: 6 Cost: 24.0 by applying add3

> State: (15) Depth: 5 Cost: 20.0 by applying add3

> State: (12) Depth: 4 Cost: 16.0 by applying add3

> State: (9) Depth: 3 Cost: 12.0 by applying add3

> State: (6) Depth: 2 Cost: 8.0 by applying add3

> State: (3) Depth: 1 Cost: 4.0 by applying add3

> Starting at state: (0)

>

> Generalized missionaries and cannibals (3,3,1)

> Breadth-first search skipping repeated states

> State: (0:3,0:3,0:1) Depth: 11 Cost: 11.0 by applying (0,2,-1)

> State: (0:3,2:1,1:0) Depth: 10 Cost: 10.0 by applying (0,1,1)

> State: (0:3,1:2,0:1) Depth: 9 Cost: 9.0 by applying (0,2,-1)

> State: (0:3,3:0,1:0) Depth: 8 Cost: 8.0 by applying (0,1,1)

> State: (0:3,2:1,0:1) Depth: 7 Cost: 7.0 by applying (2,0,-1)

> State: (2:1,2:1,1:0) Depth: 6 Cost: 6.0 by applying (1,1,1)

> State: (1:2,1:2,0:1) Depth: 5 Cost: 5.0 by applying (2,0,-1)

> State: (3:0,1:2,1:0) Depth: 4 Cost: 4.0 by applying (0,1,1)

> State: (3:0,0:3,0:1) Depth: 3 Cost: 3.0 by applying (0,2,-1)

> State: (3:0,2:1,1:0) Depth: 2 Cost: 2.0 by applying (0,1,1)

> State: (3:0,1:2,0:1) Depth: 1 Cost: 1.0 by applying (0,2,-1)

> Starting at state: (3:0,3:0,1:0)

>

> Breadth-first search with repeated states

> State: (0:3,0:3,0:1) Depth: 11 Cost: 11.0 by applying (0,2,-1)

> State: (0:3,2:1,1:0) Depth: 10 Cost: 10.0 by applying (0,1,1)

> State: (0:3,1:2,0:1) Depth: 9 Cost: 9.0 by applying (0,2,-1)

> State: (0:3,3:0,1:0) Depth: 8 Cost: 8.0 by applying (0,1,1)

> State: (0:3,2:1,0:1) Depth: 7 Cost: 7.0 by applying (2,0,-1)

> State: (2:1,2:1,1:0) Depth: 6 Cost: 6.0 by applying (1,1,1)

> State: (1:2,1:2,0:1) Depth: 5 Cost: 5.0 by applying (2,0,-1)

> State: (3:0,1:2,1:0) Depth: 4 Cost: 4.0 by applying (0,1,1)

> State: (3:0,0:3,0:1) Depth: 3 Cost: 3.0 by applying (0,2,-1)

> State: (3:0,2:1,1:0) Depth: 2 Cost: 2.0 by applying (0,1,1)

> State: (3:0,1:2,0:1) Depth: 1 Cost: 1.0 by applying (0,2,-1)

> Starting at state: (3:0,3:0,1:0)

>

> A* Search:

> State: (0:3,0:3,0:1) Depth: 11 Cost: 11.0 by applying (0,2,-1)

> State: (0:3,2:1,1:0) Depth: 10 Cost: 10.0 by applying (0,1,1)

> State: (0:3,1:2,0:1) Depth: 9 Cost: 9.0 by applying (0,2,-1)

> State: (0:3,3:0,1:0) Depth: 8 Cost: 8.0 by applying (0,1,1)

> State: (0:3,2:1,0:1) Depth: 7 Cost: 7.0 by applying (2,0,-1)

> State: (2:1,2:1,1:0) Depth: 6 Cost: 6.0 by applying (1,1,1)

> State: (1:2,1:2,0:1) Depth: 5 Cost: 5.0 by applying (2,0,-1)

> State: (3:0,1:2,1:0) Depth: 4 Cost: 4.0 by applying (0,1,1)

> State: (3:0,0:3,0:1) Depth: 3 Cost: 3.0 by applying (0,2,-1)

> State: (3:0,2:1,1:0) Depth: 2 Cost: 2.0 by applying (0,1,1)

> State: (3:0,1:2,0:1) Depth: 1 Cost: 1.0 by applying (0,2,-1)

> Starting at state: (3:0,3:0,1:0)

>

> Greedy Search:

> State: (0:3,0:3,0:1) Depth: 11 Cost: 11.0 by applying (0,2,-1)

> State: (0:3,2:1,1:0) Depth: 10 Cost: 10.0 by applying (0,1,1)

> State: (0:3,1:2,0:1) Depth: 9 Cost: 9.0 by applying (0,2,-1)

> State: (0:3,3:0,1:0) Depth: 8 Cost: 8.0 by applying (0,1,1)

> State: (0:3,2:1,0:1) Depth: 7 Cost: 7.0 by applying (2,0,-1)

> State: (2:1,2:1,1:0) Depth: 6 Cost: 6.0 by applying (1,1,1)

> State: (1:2,1:2,0:1) Depth: 5 Cost: 5.0 by applying (2,0,-1)

> State: (3:0,1:2,1:0) Depth: 4 Cost: 4.0 by applying (0,1,1)

> State: (3:0,0:3,0:1) Depth: 3 Cost: 3.0 by applying (0,2,-1)

> State: (3:0,2:1,1:0) Depth: 2 Cost: 2.0 by applying (0,1,1)

> State: (3:0,1:2,0:1) Depth: 1 Cost: 1.0 by applying (0,2,-1)

>

>

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