prolog代写-COMP3411/9814-Assignment 1

COMP3411/9814 Artificial Intelligence
Term 1, 2021
DRAFT
Assignment 1 – Prolog and Search
Due: Friday 19 March, 10:00 pm
Marks: 20% of final assessment for COMP3411/9814 Artificial Intelligence
Part 1 - PrologIn this part, you are to write some Prolog programs. At the top of your 8ile, place a comment containing your full name, student
number and assignment name. You may add additional information like the date the program was completed, etc. if you wish. At the start of each Prolog predicate, write a comment describing the operation of the predicate.
Testing Your Code A signi8icant part of completing this assignment will be testing the code you write to make sure that it works correctly. To do this, you will need to design test cases that exercise every part of the code. You should pay particular attention to "boundary cases", that is, what happens when the data you are testing with is very small, or in some way special. For example:
• What happens when the list you input has no members, or only one member?
• Does you code work for lists with both even and odd numbers of members?
• Does your code work for negative numbers? Note: not all of these matter in all cases, so for example with sqrt_table, negative numbers don't have square roots, so it doesn't make sense to ask whether your code works with negative numbers. With each question, some example test data are provided to clarify what the code is intended to do. You need to design further test data. Testing, and designing test cases, is part of the total programming task.
It is important to use exactly the names given below for your predicates,
otherwise the automated testing procedure will not be able to 9ind your
predicates and you will lose marks. Even the capitalisation of your predicate
names must be as given below.
Question 1.1: List Processing
Write a predicate sumsq_even(Numbers, Sum) that sums the squares of only the
even numbers in a list of integers.
Example:
?- sumsq_even([1,3,5,2,-4,6,8,-7], Sum).
Sum = 120
Note that it is the element of the list, not its position, that should be tested for oddness.
(The example computes 2*2 + (-4)*(-4) + 6*6 + 8*8). Think carefully about how the
predicate should behave on the empty list — should it fail or is there a reasonable value
that Sum can be bound to?
To decide whether a number is even or odd, you can use the built-in Prolog operator N
mod M, which computes the remainder after dividing the whole number N by the whole
number M. Thus a number N is even if the goal 0 is N mod 2 succeeds. Remember that
arithmetic expressions like X + 1 and N mod M are only evaluated, in Prolog, if they
appear after the is operator. So 0 is N mod 2 works, but N mod 2 is 0 doesn't work.
Question 1.2: List Processing
Eliza was the name of the first “chatbot” written by Joseph Weizenbaum at MIT in the
mid-1960s. It pretended to be a psychiatrist, so that it only had to do simple
transformations on the input and turn a statement into a sentence. If a sentence is
represented by a list of words, an example of a simple transformation is:
?- eliza1([you,do,not,like,me], X).
X = [what,makes,you,say,i,do,not,like,you]
Here, the simple transformation is to put “What makes you say” in the front of the
sentence and replace “you” with “i” and “me” with “you”.
Write a Prolog program that takes a sentence in the form of a list and replaces any
occurrence:
you → i
me → you
my → your
and prepends the list [what, makes, you, say] to the transformed list.
Note 1: your predicate MUST be called “eliza1”. Don’t forget the “1”.
Note 2: To prevent trying to print lists that are accidentally too long, SWI Prolog
limits the number of elements in a list that it prints. You might see the answer to your
query ending with [a, b c | …]. You can force SWI Prolog to print longer lists with the
directive
which you can put at the top of your file. max_depth(0) means no limit.
Question 1.3: List Processing
The rules in Question 1.2 work if “you” starts a sentence but won’t make much sense
for an example like this:
?- eliza1([i,wonder,if,you,would,help,me,learn,prolog], X).
X = [what,makes,you,say,i,if,wonder,i,would,help,you,learn,prolog]
What would be better is:
?- eliza2([i,wonder,if,you,would,help,me,learn,prolog], X).
X = [what,makes,you,think,i,would,help,you]
Write a predicate eliza2 (don’t forget the “2”) that takes a list of words:
[ …, you, , me, …]
and creates a new list of the form:
[what, makes, you, think, i, , you]
i.e. skip the words before “you” and after “me”, and insert the words in between “you”
and “me” into the new sentence between “i” and “you”.
Hint: You can use the built-in predicate “append(X, Y, Z)” to do a lot of the work for
you. Remember, “append” can be used to split a list, as well as concatenating lists.
Question 1.4: Prolog Terms
Arithmetic expressions can be written in prefix format, e.g 1+2*3 can be written as
add(1, mul(2, 3)). If the operators available are add, sub, mul, div, write a
Prolog program, eval(Expr, Val), that will evaluate an expression, e.g.
V = 7
?- eval(div(add(1, mul(2, 3)), 2), V).
V = 3.5
Testing
This assignment will be marked on functionality in the first instance. However, you
should always adhere to good programming practices in regard to structure, style and
comments, as described in the Prolog Dictionary. Submissions that score very low in the
automarking will be examined by a human marker, and may be awarded a few marks,
Your code must work under the version of SWI Prolog used on the Linux machines in
the UNSW School of Computer Science and Engineering. If you develop your code on
any other platform, it is your responsibility to re-test and, if necessary, correct your code
when you transfer it to a CSE Linux machine prior to submission.
Your code will be run on a few simple tests when you submit. So, it is a good idea to
submit early and often so that potential problems with your code can be detected early.
You will be notified at submission time if your code produces any compiler warnings.
Please ensure that your final submission does not produce any such warnings
(otherwise, marks will be deducted).
Part 2 - Search
Question 1: Search Algorithms for the 15-Puzzle In this question you will construct a table showing the number of states expanded when the 15-puzzle is solved, from various starting positions, using four different searches:
(i) Uniform Cost Search (with Dijkstra’s Algorithm)
(ii) Iterative Deepening Search
(iii) A*Search (using the Manhattan Distance heuristic)
(iv) Iterative Deepening A* Search
Go to theWebCMS. Under “Assignments” you will find Prolog Search Code
“prolog_search.zip”. Unzip the file and change directory to prolog search, e.g.
unzip prolog_search.zip
cd prolog_search
Start prolog and load puzzle15.pl and ucsdijkstra.pl by typing
[puzzle15].
[ucsdijkstra].
Then invoke the search for the specified start10 position by typing
start10(Pos),solve(Pos,Sol,G,N),showsol(Sol).
When the answer comes back, just hit Enter/Return. This version of Uniform Cost
Search (UCS) uses Dijkstra’s algorithm which is memory efficient, but is designed to
return only one answer. Note that the length of the path is returned as G, and the total
number of states expanded during the search is returned as N.
a) Draw up a table with four rows and five columns. Label the rows as UCS, IDS, A*
and IDA*, and the columns as start10, start12, start20, start30
and start40. Run each of the following algorithms on each of the 5 start states:

(i)[ucsdijkstra]
(ii)[ideepsearch]
(iii)[astar]
(iv)[idastar]
In each case, record in your table the number of nodes generated during the search.
If the algorithm runs out of memory, just write “Mem” in your table. If the code
runs for five minutes without producing out- put, terminate the process by typing
Control-C and then “a”, and write “Time” in your table. Note that you will need to
re-start prolog each time you switch to a different search.
b) Briefly discuss the efficiency of these four algorithms (including both time and
memory usage).
Question 2: Heuristic Path Search for 15-Puzzle
In this question you will be exploring an Iterative Deepening version of the Heuristic
Path Search algorithm discussed in the Week 3 Tutorial. Draw up a table in the
following format:

The top row of the table has been filled in for you (to save you from running some
rather long computations). (a) Run [greedy] forstart50, start60 and start64, and record the values returned for G
and N in the last row of your table (using the Manhattan Distance heuristic defined
in puzzle15.pl).
(b) Now copy idastar.pl to a new file heuristic.pl and modify the code of this new file so
that it uses an Iterative Deepening version of the Heuristic Path Search algorithm
discussed in the Weak 2 Tutorial Exercise, with w = 1.2 .
In your submitted document, briefly show the section of code that was changed, and
the replacement code.
(c) Run [heuristic] on start50, start60 and start64 and record the values of G and N in
your table. Now modify your code so that the value of w is 1.4, 1.6 ; in each case,
run the algorithm on the same three start states and record the values of G and N in
(d) Briefly discuss the tradeoff between speed and quality of solution for these five
algorithms.
Your submission will consist of two files: assign1_part1.pl should contain all of your
Prolog programs; and assign1_part2.pdf should contain the results of your search
experiments in part 2.
To hand in, log in to a School of CSE Linux workstation or server, make sure that your
files are in the current working directory, and use the Unix command:
% give cs3411 assign1 assign1_part1.pl assign1_part2.pdf
In each case, record in your table the number of nodes generated dur-
ing the search. If the algorithm runs out of memory, just write “Mem”
in your table. If the code runs for five minutes without producing out-
put, terminate the process by typing Control-C and then “a”, and write
“Time” in your table. Note that you will need to re-start prolog each
time you switch to a different search.
(b) Briefly discuss the efficiency of these four algorithms (including both time
and memory usage).
Question 2: Heuristic Path Search for 15-Puzzle (2 marks)
In this question you will be exploring an Iterative Deepening version of the
Heuristic Path Search algorithm discussed in the Week 4 Tutorial. Draw up
a table in the following format:
start50 start60 start64
IDA∗ 50 14642512 60 321252368 64 1209086782
1.2
1.4
1.6
Greedy
The top row of the table has been filled in for you (to save you from running
some rather long computations).
(a) Run [greedy] for start50, start60 and start64, and record the values
returned for G and N in the last row of your table (using the Manhattan
Distance heuristic defined in puzzle15.pl).
(b) Now copy idastar.pl to a new file heuristic.pl and modify the code of
this new file so that it uses an Iterative Deepening version of the Heuristic
Path Search algorithm discussed in the Week 4 Tutorial Exercise, with
w = 1.2 .
In your submitted document, briefly show the section of code that was
changed, and the replacement code.
(c) Run [heuristic] on start50, start60 and start64 and record the
values of G and N in your table. Now modify your code so that the value
of w is 1.4, 1.6 ; in each case, run the algorithm on the same three start
states and reco d the values of G and N in your table.
(d) Briefly discuss the tradeoff between speed and quality of solution for
these five algorithms.
2
Please make sure your code works on CSE's Linux machines and generates no
warnings. Remove all test code from your submission. Make sure you have named
You can submit as many times as you like - later submissions will overwrite earlier
ones. Once give has been enabled, you can check that your submission has been
received by using one of these commands:
The submission deadline is Friday 19 March, 10:00 pm.
10% penalty will be applied to the (maximum) mark for every 24 hours late after the
Questions relating to the project can be posted to the forums on the course Web site.
If you have a question that has not already been answered on the forum, you can email
it to cs3411@unsw.edu.au
Plagiarism Policy
Group submissions are not allowed. Your program must be entirely your own work.
Plagiarism detection software will be used to compare all submissions pairwise
(including submissions for any similar projects from previous years) and serious
penalties will be applied, particularly in the case of repeat offences.
DO NOT COPY FROM OTHERS. DO NOT ALLOW ANYONE TO SEE YOUR
CODE
Please refer to the UNSW Policy on Academic Honesty and Plagiarism if you require
further clarification on this matter.