» Assignments » Assignment 3: Ataxx
In this assignment, you will develop an AI that plays Ataxx, a strategy board game from 1990. 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 7 June, 2020, at 11:00pm Canberra time sharp
Overview of Tasks
This assignment is marked out of 100 for COMP1100, and out of 120 for COMP1130:
As with assignment 2, code that does not compile will be penalised heavily. This means that both the commands cabal v2-run game (with sensible arguments) and cabal v2-test must run without errors. If either if those commands fail with an error, a heavy mark deduction will be applied. 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 clone it to your computer, following the same steps as in Lab 2. The assignment repository is at https://gitlab.cecs.anu.edu.au/comp1100/2020s1studentfiles/assignment3.git.
This assignment uses a newer version of the codeworld-api package. Run cabal v2-update so that cabal knows about the new codeworld-api version, and then cabal v2-build so that it can download and build codeworld-api and other libraries. Continue reading this specification while it works in the background.
Overview of the Game
Ataxx is played on a grid of squares – usually 7×7, but COMP1130 students will have a larger 9×9 board to create additional challenge. Here is how the 7×7 board looks at the start of the game:
Task
COMP1100
COMP1130
Main Task: Ataxx AI
55 Marks
65 Marks
Unit Tests
10 Marks
10 Marks
Style
10 Marks
10 Marks
Technical Report
25 Marks
35 Marks
There are four types of squares on the board:
Empty squares can be occupied by a piece;
White discs are Player 1’s pieces;
Black discs are Player 2’s pieces; and
Grey squares are immovable blocks. Thesse prevent a disk from entering that space, but may be jumped over.
White moves first. On your turn, you move one of your pieces in one of two ways:
Copy your piece into an adjacent empty square (this includes diagonals, for up to 8 possible moves), or
Jump your piece into an empty square two spaces away.
After your piece finishes moving, it captures any adjacent enemy pieces, turning them into more pieces of your colour.
This diagram shows the relationship between moving and capturing. The white piece in the red circle can duplicate itself into four spaces (marked with the black “D”), jump into fourteen spaces (marked with a “J”), and in four of those cases (marked with a red “J”) will land next to a black piece and capture it. The dark grey squares are immovable blocks – no piece can occupy that space, but it can be jumped over.
The game continues until one of two things are true:
A player cannot make a move (because there’s no free space, none of that player’s pieces able to move, or all of that player’s pieces have been captured), or
The board reaches a state which it has already been in at some earlier point in the game. This guards against players are jumping pieces back and forth, but not capturing.
In the first case, the winner is the player with the greatest number of pieces on the board. In the second case, the game ends in a draw.
Overview of the Repository
Most of your code will be written in src/AI.hs, but you will also need to write tests in src/AITests.hs.
Other Files
src/Ataxx.hs implements the rules of Ataxx. You should read over this file and familiarise yourself with the data declarations and the type signatures of the functions in it, as you will use these to analyse the game states. You do not need to understand how every function in this file works in detail.
src/AtaxxTests.hs implements some unit tests for the Ataxx game. You are welcome to read through it.
src/Testing.hs is a simple test framework like the one in Assignment 2. It has been extended so that you can group related
tests together for clarity.
src/Dragons contains all the other code that makes the framework go. You do not need to read or understand anything in this directory. (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.)
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.
comp1100-assignment3.cabal tells the cabal build tool how to build your assignment. We will discuss how to use cabal below.
.ghcid tells the ghcid tool which command to run, which is what supplies VSCodium with error highlighting that automatically updates when you save a file.
.gitignore tells git which files it should not put into version control. These are often generated files, so it doesn’t make sense to place them under version control.
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 v2-build: Compile your assignment.
cabal v2-run game: Build your assignment (if necessary), and run 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 v2-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.
cabal v2-haddock: Generate documentation in HTML format, which you can read with a web browser. This might be a nice
way to read a summary of the Ataxx module, but it also documents the Dragons modules which you can safely ignore.
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 a terminal from VSCodium).
Overview of the Test Program
To run the test program, you need to provide it with command line arguments that tell it who is playing. The command you run will
depend on your course, but here is an example. This command will let you play against the firstLegalMove AI: cabal v2-run game — –p1 human –p2 ai:firstLegalMove
COMP1130 students should add –comp1130 to the end, so that their game is played on the larger board. In general, the command to run the game looks like this:
cabal v2-run game — ARGS
Replace ARGS with a collection of arguments from the following list: –comp1130: Play on the larger board for the COMP1130 students.
–timeout DURATION: Change the amount of time (in decimal seconds) that AI functions are given (default = 4.0). You may want to set this to a smaller number when testing your program, so that things run faster.
–debug-lookahead: When an AI is done thinking, print out how many moves ahead it considered, and the candidate move it came up with at each level of lookahead. The first item in the printed list is the move it came up with at lookahead 1, the second item is the move it came up with at lookahead 2, and so on.
–ui codeworld: Show the game using CodeWorld. This is the default user interface. Use your web browser to play the game, as in previous assignments. Unlike the codeworld programs in previous assignments, you must terminate the program with Ctrl-C and restart it if you want to restart your game.
–ui text: Show the game in the terminal.
–ui json: Run a non-interactive game (i.e., AI vs. AI, or AI vs. network), and output a report of the game in JSON format.
You probably won’t have a use for this, but it’s documented here for completeness.
–host PORT: Listen for a network connection on PORT. You only need this for network play (below). –connect HOST:PORT: Connect to someone else’s game. You only need this for network play (below). –player1 PLAYER: Specify the white player. Required.
–player2 PLAYER: Specify the black player. Required.
The PLAYER parameters describe who is playing, and can take one of the following forms:
Network Play
Network play is provided in the hope that it will be useful, but we are unable to provide support for this feature, or diagnose problems related to tunnelling network connections between computers.
The assignment framework supports network play, so that you can test AIs against each other without sharing code. One machine must host the game, and the other machine must connect to the game. In the example below, machine A hosts a game on port 5000 with the AI crashOverride as player 1, then machine B connects to the game, providing the AI acidBurn as player 2:
Format
Effect
human
Ask the person at the computer for moves.
ai
Ask the “default” AI for moves.
ai:AINAME
Ask a specific AI for moves (example: ai:firstLegalMove).
network
Wait for a move from the network.
# On Machine A:
cabal v2-run game — –host 5000 –p1 ai:crashOverride –p2 network
# On Machine B (you’ll need Machine A’s external IP address somehow):
cabal v2-run game — –connect 198.51.100.66:5000 –p1 network –p2 ai:acidBurn
Under the hood, the network code makes a single TCP connection, and moves are sent over the network in JSON. You will need to set up your modem/router to forward connections to the machine running your assignment. A service like ngrok may help, but as previously mentioned we are unable to provide any support for this feature.
Main Task: Ataxx AI (COMP1100 55 Marks; COMP1130 65 Marks)
Implement an AI (of type AIFunc, defined 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. This list is also where the framework looks when it tries to load an AI by name.
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 AIFunc Type
The AIFunc type has two constructors, depending on whether you are implementing a simple AI that looks only at the current
state, or a more complicated AI that performs look-ahead.
The NoLookahead constructor takes as its argument a function of type GameState -> Move. That is, the function you provide should look at the current state of the game and return the move to play. This constructor is intended for very simple AIs that do not look ahead in the game tree.
The WithLookahead constructor takes as its argument a function of type GameState -> Int -> Move. The Int parameter may be used to represent how many steps you should try to look ahead in the game tree. The assignment framework will call your function over and over, with look-ahead 1, then 2, then 3, etc., until it runs out of time. The framework will take the result of the most recent successful function call as your AI’s best move. If your AI does not return a move in time, the program will stop with an error.
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.
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:
Look-ahead: 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 look-ahead, a move may let you capture a lot of pieces, but at deeper look-ahead 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 achieve a deeper look-ahead 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/AttaxTest.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 think about the problem and your solution to it.
Your Task
Ensure that your code is written in good Haskell style.
Technical Report (COMP1100: 25 Marks; COMP1130: 35 Marks) You are to write a concise technical report about your assignment.
The maximum word count is 1500 for COMP1100 students, and 2500 for COMP1130 students. 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 tutors Your university ID
An excellent report will:
Demonstrate a 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 the concepts taught in this course. 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 a 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?
Assumptions
Describe any assumptions that you needed to make, and how they have 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 (i.e. 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?
Again, be specific – did you just check that you can draw the triangles and polygons from Task 1, or did you come up with additional examples?
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 them. Try to 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 VSCodium.
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
Recounting 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 and do not share detailed descriptions of your design. 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.
Course staff will not look at assignment code unless it is posted privately in Piazza, or in a drop-in consultation.
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 you 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 by using your browser to visit https://gitlab.cecs.anu.edu.au/uXXXXXXX/assignment3, where XXXXXXX is your student number.
Ensure your program compiles and runs, including the cabal v2-test test suite. 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 successfully added it in GitLab.
UPDATED: 16 May 2020 / RESPONSIBLE OFFICER: Director, RSCS / PAGE CONTACT: Course Convenor