yap-6.3/Logtalk/examples/searching/SCRIPT

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Logtalk - Object oriented extension to Prolog
Release 2.25.0

Copyright (c) 1998-2005 Paulo Moura.  All Rights Reserved.
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% start by loading the necessary library and support example files (if not 
% already loaded):

| ?- logtalk_load(library(all_loader)).
...

| ?- logtalk_load(roots(loader)).
...


% now you are ready for loading the example:

| ?- logtalk_load(searching(loader)).
...


% farmer, cabbage, goat and wolf problem

| ?- farmer::initial_state(Initial), depth_first(10)::solve(farmer, Initial, Path), farmer::print_path(Path).

cgwf.<__>..........____
c_w_..........<__>.f_g_
c_wf.<__>..........__g_
__w_..........<__>.fcg_
_gwf.<__>.........._c__
_g__..........<__>.fc_w
_g_f.<__>.........._c_w
____..........<__>.fcgw

Path = [(north,north,north,north),(north,south,north,south),(north,south,north,north),(south,south,north,south),(south,north,north,north),(south,north,south,south),(south,north,south,north),(south,south,south,south)],
Initial = (north,north,north,north) ? 

yes


% missionaires and cannibals problem, solved using a hill-climbing strategy

| ?- miss_cann::initial_state(Initial), hill_climbing(16)::solve(miss_cann, Initial, Path, Cost), miss_cann::print_path(Path).

MMMCCC.<__>..........
MMCC..........<__>.MC
MMMCC.<__>..........C
MMM..........<__>.CCC
MMMC.<__>..........CC
MC..........<__>.MMCC
MMCC.<__>..........MC
CC..........<__>.MMMC
CCC.<__>..........MMM
C..........<__>.MMMCC
CC.<__>..........MMMC
..........<__>.MMMCCC

Cost = 15,
Path = [((3,3),left,0,0),((2,2),right,1,1),((3,2),left,0,1),((3,0),right,0,3),((3,1),left,0,2),((1,1),right,2,2),((2,2),left,1,1),((0,2),right,3,1),((0,3),left,3,0),((0,1),right,3,2),((0,2),left,3,1),((0,0),right,3,3)],
Initial = ((3,3),left,0,0)
yes


% same problem as above with the addition of a monitor to measure hill-climbing performance

| ?- performance::init, miss_cann::initial_state(Initial), hill_climbing(16)::solve(miss_cann, Initial, Path, Cost), miss_cann::print_path(Path), performance::report.

MMMCCC.<__>..........
MMCC..........<__>.MC
MMMCC.<__>..........C
MMM..........<__>.CCC
MMMC.<__>..........CC
MC..........<__>.MMCC
MMCC.<__>..........MC
CC..........<__>.MMMC
CCC.<__>..........MMM
C..........<__>.MMMCC
CC.<__>..........MMMC
..........<__>.MMMCCC
solution length: 12
number of state transitions: 26
ratio solution length / state transitions: 0.461538
minimum branching degree: 1
average branching degree: 2.30769
maximum branching degree: 3
time: 0.02

Cost = 15,
Path = [((3,3),left,0,0),((2,2),right,1,1),((3,2),left,0,1),((3,0),right,0,3),((3,1),left,0,2),((1,1),right,2,2),((2,2),left,1,1),((0,2),right,3,1),((0,3),left,3,0),((0,1),right,3,2),((0,2),left,3,1),((0,0),right,3,3)],
Initial = ((3,3),left,0,0) ? 

yes


% bridge problem, solved using a hill climbing strategy

| ?- performance::init, bridge::initial_state(Initial), hill_climbing(30)::solve(bridge, Initial, Path, Cost), bridge::print_path(Path), performance::report.

 _|____________|_ lamp 1 3 6 8 12 
1 3  lamp _|____________|_ 6 8 12 
3  _|____________|_ lamp 1 6 8 12 
1 3 6  lamp _|____________|_ 8 12 
3 6  _|____________|_ lamp 1 8 12 
3 6 8 12  lamp _|____________|_ 1 
6 8 12  _|____________|_ lamp 1 3 
1 3 6 8 12  lamp _|____________|_ 
solution length: 8
state transitions: 367
ratio solution length / state transitions: 0.0217984
minimum branching degree: 1
average branching degree: 7.32579
maximum branching degree: 15
time: 0.28

Initial = [], right, [1, 3, 6, 8, 12]
Path = [ ([], right, [1, 3, 6, 8, 12]), ([1, 3], left, [6, 8, 12]), ([3], right, [1, 6, 8, 12]), ([1, 3, 6], left, [8, 12]), ([3, 6], right, [1, 8|...]), ([3, 6|...], left, [1]), ([6|...], right, [...|...]), ([...|...], ..., ...)]
Cost = 29 

yes


% water jugs problem solved using a breadth and a depth first strategy, with performance monitors
% it's interesting to compare the results

| ?- performance::init, water_jug::initial_state(Initial), breadth_first(6)::solve(water_jug, Initial, Path), water_jug::print_path(Path), performance::report.

4-gallon jug: 0
3-gallon jug: 0

4-gallon jug: 0
3-gallon jug: 3

4-gallon jug: 3
3-gallon jug: 0

4-gallon jug: 3
3-gallon jug: 3

4-gallon jug: 4
3-gallon jug: 2

4-gallon jug: 0
3-gallon jug: 2

solution length: 6
number of state transitions: 109
ratio solution length / state transitions: 0.0550459
minimum branching degree: 2
average branching degree: 3.63158
maximum branching degree: 4
time: 0.02

Path = [(0,0),(0,3),(3,0),(3,3),(4,2),(0,2)],
Initial = (0,0) ? 

yes


| ?- performance::init, water_jug::initial_state(Initial), depth_first(10)::solve(water_jug, Initial, Path), water_jug::print_path(Path), performance::report.

4-gallon jug: 0
3-gallon jug: 0

4-gallon jug: 4
3-gallon jug: 0

4-gallon jug: 4
3-gallon jug: 3

4-gallon jug: 0
3-gallon jug: 3

4-gallon jug: 3
3-gallon jug: 0

4-gallon jug: 3
3-gallon jug: 3

4-gallon jug: 4
3-gallon jug: 2

4-gallon jug: 0
3-gallon jug: 2

solution length: 8
number of state transitions: 12
ratio solution length / state transitions: 0.666667
minimum branching degree: 1
average branching degree: 2
maximum branching degree: 3
time: 0.00

Path = [(0,0),(4,0),(4,3),(0,3),(3,0),(3,3),(4,2),(0,2)],
Initial = (0,0) ? 

yes


% eight puzzle solved using a hill-climbing strategy

| ?- performance::init, eight_puzzle::initial_state(five_steps, Initial), hill_climbing(25)::solve(eight_puzzle, Initial, Path, Cost), eight_puzzle::print_path(Path), performance::report.

283
164
7 5

283
1 4
765

2 3
184
765

 23
184
765

123
 84
765

123
8 4
765
solution length: 6
number of state transitions: 15
ratio solution length / state transitions: 0.4
minimum branching degree: 2
average branching degree: 3.13333
maximum branching degree: 4
time: 0.01

Cost = 5,
Path = [[2/1,1/2,1/3,3/3,3/2,3/1,2/2,1/1,2/3],[2/2,1/2,1/3,3/3,3/2,3/1,2/1,1/1,2/3],[2/3,1/2,1/3,3/3,3/2,3/1,2/1,1/1,2/2],[1/3,1/2,2/3,3/3,3/2,3/1,2/1,1/1,2/2],[1/2,1/3,2/3,3/3,3/2,3/1,2/1,1/1,2/2],[2/2,1/3,2/3,3/3,3/2,3/1,2/1,1/1,1/2]],
Initial = [2/1,1/2,1/3,3/3,3/2,3/1,2/2,1/1,2/3] ? 

yes


% eight puzzle solved using a best-first strategy

| ?- performance::init, eight_puzzle::initial_state(five_steps, Initial), best_first(25)::solve(eight_puzzle, Initial, Path, Cost), eight_puzzle::print_path(Path), performance::report.

283
164
7 5

283
1 4
765

2 3
184
765

 23
184
765

123
 84
765

123
8 4
765
solution length: 6
number of state transitions: 15
ratio solution length / state transitions: 0.4
minimum branching degree: 2
average branching degree: 3.13333
maximum branching degree: 4
time: 0.02

Cost = 5,
Path = [[2/1,1/2,1/3,3/3,3/2,3/1,2/2,1/1,2/3],[2/2,1/2,1/3,3/3,3/2,3/1,2/1,1/1,2/3],[2/3,1/2,1/3,3/3,3/2,3/1,2/1,1/1,2/2],[1/3,1/2,2/3,3/3,3/2,3/1,2/1,1/1,2/2],[1/2,1/3,2/3,3/3,3/2,3/1,2/1,1/1,2/2],[2/2,1/3,2/3,3/3,3/2,3/1,2/1,1/1,1/2]],
Initial = [2/1,1/2,1/3,3/3,3/2,3/1,2/2,1/1,2/3] ? 

yes


% turn off performance monitor

| ?- performance::stop.