B551 Assignment 0: Searching and Python solution




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Part 1: Navigation
As we learned in Module 1, certain autonomous agents like to fly around the house and interrupt video
recordings at the most inopportune moments. Suppose that a house consists of a grid of N × M cells,
represented like this:
As you can see, the map consists of N lines (in this case, 6) and M columns (in this case, 7). Each cell of
the house is marked with one of four symbols: p represents the agent’s current location, X represents a wall
through which the agent cannot pass, . represents open space over which the agent can fly, and @ represents
your location (presumably with video recording in progress).
Your goal is to write a program that finds the shortest path between the agent and you. The agent can
move one square at a time in any of the four principal compass directions, and the program should find the
shortest distance between the two points and then output a string of letters (L, R, D, and U for left, right,
down, and up) indicating that solution. Your program should take a single command line argument, which
is the name of the file containing the map file. For example:
[<>djcran@tank ~] python3 route_pichu.sh map.txt
Shhhh… quiet while I navigate!
Here’s the solution I found:
You can assume that there is always exactly one p and one @ in the map file. If there is no solution, your
program should display path length -1 and not display a path.
To help get you started, we have provided some initial code that is already available in your GitHub repo.
Here’s what to do to complete the program.
1. We’ve already created a GitHub repository for you for this assignment. You can see the name of your
repository by logging into IU Github, at http://github.iu.edu/. In the upper left hand corner of
the screen, you should see a pull-down menu. Select cs-b551-sp2021. Then in the box below, you
should see a repository called youruserid-a0, (If you do not see cs-b551-sp2021 or a repository with
your userid, it probably means that did not log into GitHub to create your account during the A Few
Action Items activity during week 1 of class, so we were not able to add you to a team. Post a private
message on Q&A Community so that we can create your repo manually.)
To get started, from the SICE Linux machines, clone the github repository:
git clone git@github.iu.edu:cs-b551-sp2021/your-repo-name
If that doesn’t work, instead try:
git clone https://github.iu.edu/cs-b551-sp2021/your-repo-name
where your-repo-name is the one you found on the GitHub website above. (If neither command works,
you probably need to set up IU GitHub ssh keys. See Canvas for help.)
2. Now you should see a program called route pichu.py. We have also provided a sample map file,
map.txt. You can run our program like this:
python3 route_pichu.py map.txt
Unfortunately, the program does not work very well; it will probably enter an infinite loop and you’ll
have to press CONTROL-C to kill it. Nevertheless, the code is a good starting point, so familiarize
yourself with it. Figure out the precise search abstraction that the program is using and include it in
your report. In other words, what is the set of valid states, the successor function, the cost function,
the goal state definition, and the initial state?
3. Why does the program often fail to find a solution? Implement a fix to make the code work better,
and explain what you did in the report.
4. Complete the program so that it finds and displays the correct solution. Check the starter code
comments for specifications on the solve() function, because our autograder (and the pytest command
above) calls it directly.
Part 2: Hide-and-seek
Suppose that instead of a single agent as in Part 1, you have adopted k agents. The problem is that these
agents do not like one another, which means that they have to be positioned such that no two agents can
see one another. Write a program called arrange_pichus.py that takes the filename of a map in the same
format as Part 1 as well as a single parameter specifying the number k of agents that you have. You can
assume k ≥ 1. Assume two agents can see each other if they are on either the same row or column of the
map, and there are no walls between them. An agent can only be positioned on empty squares (marked
with .). It’s okay if agents see you, and you obscure the view between agents, as if you were a wall. Your
program should output a new version of the map, but with the agents’ locations marked with p. Note that
exactly one p will already be fixed in the input map file. If there is no solution, your program should just
display None. Here’s an example on the same sample output on the same map as in Part 1:
[<>djcran@tank ~] python3 arrange_pichus.py map.txt 9
We’ve again given you some code to get started with, but it’s not fully working; the configurations it finds
often allow agents to see one another, and it can be quite slow. Fix the code so that it works, and then try
to make it run as quickly as possible. In your report, explain the search abstraction you’ve used – what is
the state space, initial state, goal state, successor function, and cost function?
Make sure to test your program on maps other than the one we’ve given, including ones of different sizes and
shapes. Check the starter code comments for specifications on the solve() function, because our autograder
(and the pytest command above) calls it directly.
For optional extra credit, consider the same problem but where two agents can see each other if they
are on the same row, column, or diagonal and there is no wall (or you) between them. Instead of finding a
configuration for a given k, the program should in this case instead find a configuration such that the number
of agents is as large as possible. This extra credit functionality should be activated when the value of k is
specified as 0, and the output should be the same as above: a configuration with as many p’s as possible.
What to turn in
Turn in the two programs on GitHub (remember to add, commit, push) — we’ll grade whatever version
you’ve put there as of 11:59PM on the due date. Also remember to put your report in the Readme.md
file. To make sure that the latest version of your work has been accepted by GitHub, you can log into the
github.iu.edu website and browse the code online.