Pack logtalk -- logtalk-3.86.0/examples/searching/SCRIPT.txt

This file is part of Logtalk https://logtalk.org/ SPDX-FileCopyrightText: 1998-2023 Paulo Moura <pmoura@logtalk.org> SPDX-License-Identifier: Apache-2.0

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

% start by loading the example and the required library files:

| ?- 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

% missionaries 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).

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

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 (including previous solutions): 555 ratio solution length / state transitions: 0.014414414414414415 minimum branching degree: 1 average branching degree: 7.32579185520362 maximum branching degree: 15 time: 0.012381000000000086 Initial = s([], right, [1, 3, 6, 8, 12]), Path = [s([], right, [1, 3, 6, 8, 12]), s([1, 3], left, [6, 8, 12]), s([3], right, [1, 6, 8, 12]), s([1, 3, 6], left, [8, 12]), s([3, 6], right, [1, 8, 12]), s([3, 6|...], left, [1]), s([6|...], right, [1|...]), s([...|...], left, [])], 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

% salt puzzle using breadth first search

| ?- performance::init, salt(100, 500, 200)::initial_state(Initial), breadth_first(6)::solve(salt(100, 500, 200), Initial, Path), salt(100, 500, 200)::print_path(Path), performance::report.

(0, 0, 0) all_empty (0, 500, 0) fill(m1) (0, 300, 200) transfer(m1, m2) (0, 300, 0) empty(m2) (0, 100, 200) transfer(m1, m2) (100, 0, 200) transfer(m1, acc) solution length: 6 state transitions (including previous solutions): 405 ratio solution length / state transitions: 0.0148148 minimum branching degree: 1 average branching degree: 4.06863 maximum branching degree: 6 time: 0.03 Initial = (0, 0, 0, all_empty), Path = [ (0, 0, 0, all_empty), (0, 500, 0, fill(m1)), (0, 300, 200, transfer(m1, m2)), (0, 300, 0, empty(m2)), (0, 100, 200, transfer(m1, m2)), (100, 0, 200, transfer(..., ...))] .

yes

| ?- performance::init, salt(200, 250, 550)::initial_state(Initial), breadth_first(7)::solve(salt(200, 250, 550), Initial, Path), salt(200, 250, 550)::print_path(Path), performance::report.

(0, 0, 0) all_empty (0, 250, 0) fill(m1) (0, 0, 250) transfer(m1, m2) (0, 250, 250) fill(m1) (0, 0, 500) transfer(m1, m2) (0, 250, 500) fill(m1) (0, 200, 550) transfer(m1, m2) (200, 0, 550) transfer(m1, acc) solution length: 8 state transitions (including previous solutions): 2475 ratio solution length / state transitions: 0.00323232 minimum branching degree: 1 average branching degree: 4.21042 maximum branching degree: 6 time: 0.29 Initial = (0, 0, 0, all_empty), Path = [ (0, 0, 0, all_empty), (0, 250, 0, fill(m1)), (0, 0, 250, transfer(m1, m2)), (0, 250, 250, fill(m1)), (0, 0, 500, transfer(m1, m2)), (0, 250, 500, fill(...)), (0, 200, ..., ...), (200, ..., ...)] .

yes

| ?- performance::init, salt(100, 250, 550)::initial_state(Initial), breadth_first(11)::solve(salt(100, 250, 550), Initial, Path), salt(100, 250, 550)::print_path(Path), performance::report.

(0, 0, 0) all_empty (0, 0, 550) fill(m2) (0, 250, 300) transfer(m2, m1) (0, 0, 300) empty(m1) (0, 250, 50) transfer(m2, m1) (50, 250, 0) transfer(m2, acc) (50, 0, 0) empty(m1) (50, 0, 550) fill(m2) (50, 250, 300) transfer(m2, m1) (50, 0, 300) empty(m1) (50, 250, 50) transfer(m2, m1) (100, 250, 0) transfer(m2, acc) solution length: 12 state transitions (including previous solutions): 189914 ratio solution length / state transitions: 6.31865e-05 minimum branching degree: 1 average branching degree: 4.47592 maximum branching degree: 6 time: 94.44 Initial = (0, 0, 0, all_empty), Path = [ (0, 0, 0, all_empty), (0, 0, 550, fill(m2)), (0, 250, 300, transfer(m2, m1)), (0, 0, 300, empty(m1)), (0, 250, 50, transfer(m2, m1)), (50, 250, 0, transfer(..., ...)), (50, 0, ..., ...), (50, ..., ...), (..., ...)|...] .

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

yes

% turn off performance monitor

| ?- performance::stop.