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Programming as Problem Solving
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COMP1100 [2019 S2]
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1. Home » Assignments » Assignment 3: Othello
Assignment 3: Othello
In this assignment, you will develop an AI that plays Othello (also known as Reversi), a classic board game. We have implemented the rules of the game for you, but you will have to decide how best to play the game.
This assignment is worth 15% of your final grade.
Deadline: Sunday 27th October, 2019, at 11:00pm Canberra time sharp
Overview of Tasks
This assignment is marked out of 100:
Task
Marks
Main Task: Othello AI
55 Marks
Unit Tests
10 Marks
Style
10 Marks
Technical Report
25 Marks
As with assignment 2, code that does not compile will be penalised heavily. It is essential that you can write code that compiles and runs. If you have a partial solution that you cannot get working, you should comment it out and write an additional comment directing your tutor’s attention to it.
Getting Started
Fork the assignment repository and create a project for it in IntelliJ IDEA, following the same steps as in Lab 2. The assignment repository is at https://gitlab.cecs.anu.edu.au/comp1100/comp1100-assignment3.
Overview of the Game
Othello (also known as Reversi) is a board game played on an 8×8 board with 64 discs. Each disc is light on one side and dark on the other. The game starts with 4 discs in the centre of the board: two dark and two light.

To make a move, a player places a disc with their colour facing up on an unoccupied square on the board, such that it will capture at least one of the opponents discs.
Capturing occurs if the placed disc forms a line (horizontal, vertical or diagonal) that has one or more of the opponents discs on it and is ended by another of the current player’s discs, with none of the current player’s discs in-between. All of the opponents discs on this line are flipped over, becoming the current player’s discs. It is possible (and in fact quite common) for a single move to capture more than one line, and all the pieces which can be captured in a move must be captured (flipped).

The dark player plays first, and play alternates between the two players. If a player can’t make a legal move, their turn is skipped. If neither player can make a legal move, the game is over and the player with the most discs wins.
Overview of the Repository
Most of your code will be written in src/AI.hs, but you will also need to write tests in test/OthelloTests.hs. A small program to play the game (either Human vs. Human, or Human vs. AI, or AI vs. AI) is provided at app/Main.hs, and you can run it with cabal run.
src/GameState.hs implements the data structures used to implement the game rules. The game rules themselves are implemented at src/Game.hs. You should read over both these files. While you may not need to understand every detail of how they work, understanding what they do will be helpful.
The only files you are allowed to modify in your submission are src/AI.hs and test/OthelloTest.hs. Any other modifications risk changing the rules of the game, so you would be playing a different game to the one in the assignment.
For this assignment, GHC is set to be more pedantic than the previous two assignments. It will treat all warnings as errors, and you’ll only be able to write “Safe” Haskell. If you stick with the tools we’ve taught in the course, you shouldn’t notice this at all, with one exception: attempts to use trace and similar from Debug.Trace will fail to compile. We have chosen to use Safe Haskell to prevent your AIs from doing underhanded things in the tournament.
Other Files
• app/Main.hs implements an interface to play the game, and for you to test your skills against your AI. You are not required to understand it.
• comp1100-assignment3.cabal tells the cabal build tool how to build your assignment. You are not required to understand this file, and we will discuss how to use cabal below.
• src/Config.hs defines a data type used to configure the program. You do not need to understand or modify this file.
• The files under src/Dragons/ contain advanced code that you are not required to understand or modify. (On medieval maps they drew pictures of dragons or sea monsters over uncharted areas. The code in those files is beyond the areas of Haskell which this course explores.)
• test/Testing.hs is a testing library that is similar to the ones used in previous assignments. It has been extended to allow you to group related tests together.
• Setup.hs tells cabal that this is a normal package with no unusual build steps. Some complex packages (that we will not see in this course) need to put more complex code here. You are not required to understand it.
Overview of Cabal
As before, we are using the cabal tool to build the assignment code. The commands provided are very similar to last time:
• cabal build: Compile your assignment.
• cabal run othello: Build your assignment (if necessary), and run on the test program. We discuss the test program in detail below, as there are a number of ways to launch it.
• cabal repl comp1100-assignment3: Run the GHCi interpreter over your project.
• cabal test: Build and run the tests. This assignment is set up to run a unit test suite, and as with Assignment 2 you will be writing tests. The unit tests will abort on the first failure, or the first call to a function that is undefined.
You should execute these cabal commands in the top-level directory of your project: ~/comp1100/assignment3 (i.e., the directory you are in when you launch the IntelliJ Terminal tool for your project).
Overview of the Test Program
When you run cabal run othello, you play the game against your AI called “default”. This is done through a web browser, in the same way as previous CodeWorld assignments.
You can change the behavior of the program by calling it with different arguments, like this: cabal run othello — arg1 arg2 arg3…. These are the arguments you can provide:
Argument
Effect
-T GAMETYPE
Choose how to run the game: console/gui.
-t TIMEOUT
How much time to give the AI to make a move.
-p PLAYER1
Choose the AI name for the dark player, or HUMAN to play as a human.
-P PLAYER2
Choose the AI name for the light player, or HUMAN to play as a human.
-H HOSTNAME
Name of the computer to connect to for a network game.
-n PORTNUMBER
Port number to host/connect on for a network game.
-h
Print help text and exit.
Example: cabal run othello — -t 0.1 -p default will play the default AI against itself, and give it 0.1 seconds to make a move. The default AI that you get when you clone the repository plays the first legal move it can find, so playing it against itself should always look like this:

Main Task: Othello AI (55 Marks)
Your Task
Implement an AI (of type AI) for Othello in src/AI.hs. There is a list called ais in that file, and we will mark the AI you call “default” in that list.
We will test your AI’s performance by comparing it to implementations written by course staff, using a variety of standard approaches. Its performance against these AIs will form a large part of the marks for this Task.
It is vital that you indicate one AI as “default”, otherwise we will not know which one to mark.
Understanding the AI Type
The AI type is an alias for Game -> Int -> Position. The Game argument describes the current state of the game, and the Int argument is an indication of how far you might want to look ahead when searching for a good move.
You do not have to arrange for your AI to be called; any test program we provide will do so for you. When it is your AI’s turn, we will call your AI with the current game state and lookahead 1, then 2, then 3, etc, until four seconds have passed overall. The most recent result will be taken as the final result.
While you are testing, you may want to use the -t option to set a shorter timeout, so that you can test changes more quickly.
Very simple AIs that do not look ahead will ignore the Int argument.
Discussion
Your AI should inspect the Turn within the Game to see whose turn it is. You may call error if the Turn is GameOver – your AI should never be called on a finished game. Your AI can then use the Player value and opponent function to work out how to evaluate the board.
You may also assume that we will only ever call your AI if there is a legal move it can make. In particular, this means that we will not deduct marks for assuming that a list of legal moves is non-empty (e.g., you used the head function). Note that gratuitous use of head and tail is still poor style.
This is a very open-ended task, and it will probably help if you build up your solution a little at a time. We suggest some approaches below.
First Legal Move
The simplest AI you can build is one that makes the first legal move it can. We have provided this for you, so you can see what a simple AI looks like.
Interlude: Heuristics
Heuristic functions were discussed in the lecture on game trees. We expect the quality of your heuristic function – how accurately it scores game states – to have a large impact on how well your AI performs.
Greedy Strategy
“Greedy strategies” are the class of strategies that make moves that provide the greatest immediate advantage. In the context of this game, it means always making the move that will give it the greatest increase in heuristic. Try writing a simple heuristic and a greedy strategy, and see whether it beats your “first legal move” AI.
Interlude: Game Trees
To make your AI smarter, it is a good idea for it to look into the future and consider responses to its moves, its responses to those responses, and so on. The lecture on game trees may help you here.
It is possible for one player to make two moves in a row, if the opponent has no legal move. Therefore, it is not safe to assume that each layer of the game tree is scored for opposing players.
Minimax
Greedy strategies can often miss opportunities that need some planning, and get tricked into silly traps by smarter opponents. The Minimax Algorithm was discussed in the lecture on game trees and will likely give better performance than a greedy strategy.
Pruning
Once you have Minimax working, you may find that your AI exploring a number of options that cannot possibly influence the result. Cutting off branches of the search space early is called pruning, and one effective method of pruning is called Alpha-Beta Pruning, which was discussed in lectures. Good pruning may allow your search to explore deeper within the time limit it has to make its move.
Other Hints
• There are four main ways your AI can be made smarter:
◦ Lookahead: If your function runs efficiently, it can see further into the future before it runs out of time. The more moves into the future it looks, the more likely it will find good moves that are not immediately obvious. Example: at 1 level of lookahead, a move may let you capture a lot of dics, but at deeper lookahead you might see that it leaves you open to a large counter-capture.
◦ Heuristic: You will not have time to look all the way to the end of every possible game. Your heuristic function guesses how good a Game is for each player. If your heuristic is accurate, it will correctly identify strong and weak states.
◦ Search Strategy: This determines how your AI decides which heuristic state to aim for. Greedy strategies look for the best state they can (according to the heuristic) and move towards that state. More sophisticated strategies like Minimax consider the opponent’s moves when planning.
◦ Pruning: if you can discard parts of the game tree without considering them in detail, you can process game trees faster and acheive a deeper lookahead in the allotted running time. Alpha-beta pruning is one example; there are others.
• Choosing a good heuristic function is very important, as it gives your AI a way to value its position that is smarter than just looking at current score. Perhaps you might find that some squares are more valuable than others, when it comes to winning games, and so your AI should value them more highly.
• Do not try to do everything at once. This does not work in production code and often does not work in assignment code either. Get something working, then take your improved understanding of the problem to the more complex algorithms.
• As you refine your AIs, test them against each other to see whether your changes are actually an improvement.
Unit Tests (10 Marks)
As with Assignment 2, you will be expected to write unit tests to convince yourself that your code is correct. The testing code has been extended from last time – test/Testing.hs now allows you to group tests into a tree structure. As before, you run the tests using cabal test.
Your Task
Add tests to test/OthelloTest.hs that test your AI.
Hints
• Most of the hints from Assignment 2 apply here. Reread those.
• If a function is giving you an unexpected result, try breaking it into parts and writing tests for each part. This helps you isolate the incorrect parts, and gives you smaller functions to fix.
• If your function has subtle details that need to be correct, think about writing tests to ensure those details do not get missed as you work on your code.
Style (10 Marks)
As you write increasingly complex code, it is increasingly important that the code remains readable. This saves wasted effort understanding messy code, which makes it easier to think about the problem and your solution to it.
Your Task
Ensure that your code is written in good Haskell style.
Technical Report (COMP1100: 15 marks)
You should write a concise technical report. An excellent report will: demonstrate conceptual understanding of all major functions, and how they interact when the program as a whole runs; explain your design process, including your assumptions, and the reasons behind choices you made; discuss how you tested your program, and in particular why your tests give you confidence that your code is correct; and be well formatted without spelling or grammar errors.
The maximum word count is 1500. This is a limit, not a quota; concise presentation is a virtue.
Once again: This is not a required word count. They are the maximum number of words that your marker will read. If you can do it in fewer words without compromising the presentation, please do so.
Your report must be in PDF format, located at the root of your assignment repository on GitLab and named Report.pdf. Otherwise, it may not be marked.
The report must have a title page with the following items:
• Your name
• Your laboratory time and tutor
• Your university ID
An excellent report will:
• demonstrate conceptual understanding of all major functions, and how they interact when the program as a whole runs;
• explain your design process, including your assumptions, and the reasons behind choices you made;
• discuss how you tested your program, and in particular why your tests give you confidence that your code is correct; and
• be well formatted without spelling or grammar errors.
Content and Structure
Your audience is the tutors and lecturers, who are proficient at programming and understand most concepts. Therefore you should not, for example, waste words describing the syntax of Haskell or how recursion works. After reading your technical report, the reader should thoroughly understand what problem your program is trying to solve, the reasons behind major design choices in it, as well as how it was tested. Your report should give a broad overview of your program, but focus on the specifics of what you did and why.
Remember that the tutors have access to the above assignment specification, and if your report only contains details from it then you will only receive minimal marks. Below is an potential outline for the structure of your report and some things you might discuss in it.
Introduction
If you wish to do so you can write an introduction. In it, give:
• A brief overview of your program:
◦ how it works; and
◦ what it is designed to do.
Content
Talk about why you structured the program the way you did. Below are some questions you could answer:
• Program design
◦ Describe what each relevant function does conceptually. (i.e. how does it get you closer to solving the problems outlined in this assignment spec?)
◦ How do these functions piece together to make the finished program? Why did you design and implement it this way?
◦ What major design choices did you make regarding the functions that you’ve written, and the overall structure of your program?
◦ For this assignment specifically, you could also ask yourself:
▪ How does your AI select a good move?
▪ What data structures did you choose, and why?
▪ How did you develop the AI that is your main submission?
• Assumptions
◦ Describe assumptions you have made and how this has influenced your design decisions.
• Testing
◦ How did you test individual functions?
▪ Be specific about this – the tutors know that you have tested your program, but they want to know how.
▪ Describe the tests that prove individual functions on their own behave as expected (e.g. testing a function with different inputs and doing a calculation by hand to check that the outputs are correct).
◦ How did you test the entire program? What tests did you perform to show that the program behaves as expected in all (even unexpected) cases?
• Inspiration / external content
◦ What resources did you use when writing your program (e.g., published algorithms)?
◦ If you have used resources such as a webpage describing an algorithm, be sure to cite it properly at the end of your report in a ‘References’ section. References do not count to the maximum word limit.
Reflection
Discuss the reasoning behind your decisions, rather than what the decisions were. You can reflect on not only the decisions you made, but the process through which you developed the final program:
• Did you encounter any conceptual or technical issues?
◦ If you solved them, describe the relevant details of what happened and how you overcame them.
◦ Sometimes limitations on time or technical skills can limit how much of the assignment can be completed. If you ran into a problem that you could not solve, then your report is the perfect place to describe it. You could include details such as:
▪ Theories as to what caused the problem;
▪ Suggestions of things that might have fixed it; and
▪ Discussion about what you did try, and the results of these attempts.
• What would you have done differently if you were to do it again?
◦ What changes to the design and structure you would make if you wrote the program again from scratch?
• Are parts of the program confusing for the reader? You can explain them in the report (in this situation you should also make use of comments in your code).
• If you collaborated with others, what was the nature of the collaboration? (Note that you are only allowed to collaborate by sharing ideas, not code.)
◦ Collaborating is any discussion or work done together on planning or writing your assignment.
• Other info
◦ You may like to briefly discuss details of events which were relevant to your process of design – strange or interesting things that you noticed and fixed along the way.
This is a list of suggestions, not requirements. You should only discuss items from this list if you have something interesting to write.
Things to avoid in a technical report
• Line by line explanations of large portions of code. (If you want to include a specific line of code, be sure to format as described in the “Format” section below.)
• Pictures of code or IntelliJ.
• Content that is not your own, unless cited.
• Grammatical errors or misspellings. Proof-read it before submission.
• Informal language – a technical report is a professional document, and as such should avoid things such as:
◦ Unnecessary abbreviations (atm, btw, ps, and so on), emojis, and emoticons; and
◦ Stories / recounts of events not relevant to the development of the program.
• Irrelevant diagrams, graphs, and charts. Unnecessary elements will distract from the important content. Keep it succinct and focused.
If you need additional help with report writing, the academic skills writing centre has a peer writing service and writing coaches.
Format
You are not required to follow any specific style guide (such as APA or Harvard). However, here are some tips which will make your report more pleasant to read, and make more sense to someone with a computer science background.
• Colours should be kept minimal. If you need to use colour, make sure it is absolutely necessary.
• If you are using graphics, make sure they are vector graphics (that stay sharp even as the reader zooms in on them).
• Any code, including type/function/module names or file names, that appears in your document should have a monospaced font (such as Consolas, Courier New, Lucida Console, or Monaco)
• Other text should be set in serif fonts (popular choices are Times, Palatino, Sabon, Minion, or Caslon).
• When available, automatic ligatures should be activated.
• Do not use underscore to highlight your text.
• Text should be at least 1.5 spaced.
Communication
Do not post your code publicly, either on Piazza or via other forums. Posts on Piazza trigger emails to all students, so if by mistake you post your code publicly, others will have access to your code and you may be held responsible for plagiarism.
Once again, and we cannot stress this enough: do not post your code publicly . If you need help with your code, post it privately to the instructors.
When brainstorming with your friends, do not share code. There might be pressure from your friends, but this is for both your and their benefit. Anything that smells of plagiarism will be investigated and there may be serious consequences.
Sharing ideas and sketches is perfectly fine, but sharing should stop at ideas.
Course staff will not look at assignment code unless it is posted privately in piazza.
Course staff will typically give assistance by asking questions, directing you to relevant exercises from the labs, or definitions and examples from the lectures.
Before the assignment is due, course staff will not give individual tips on writing functions for the assignment or how your code can be improved. We will help you get unstuck by asking questions and pointing you to relevant lecture and lab material. You will receive feedback on your work when marks are released.
Submission Advice
Start early, and aim to finish the assignment several days before the due date. At least 24 hours before the deadline, you should:
• Re-read the specification one final time, and make sure you’ve covered everything.
• Confirm that the latest version of your code has been pushed to GitLab.
• Ensure your program compiles and runs, including the cabal test test suite.
• Ensure your submission works on the lab machines. If it does not, it may fail tests used by the instructors.
• Proof-read and spell-check your report.
• Verify that your report is in PDF format, in the root of the project directory (not in src), and named Report.pdf. That capital R is important – Linux uses a case-sensitive file system. Check that you have succesfully added it in GitLab.
Updated: 08 Oct 2019
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