I know! I'll use my
Higher-order functions to
Order higher rolls.
In this project, you will develop a simulator and multiple strategies for the dice game Hog. You will need to use control and higher-order functions together, from Sections 1.1 through 1.6 of the Composing Programs online text.
Developed at University of California, Berkeley by John DeNero and the CS61A staff, this project is based on a 2010 SIGCSE Nifty Assignment by Todd Neller.
In Hog, two players alternate turns trying to reach 100 points first. On each turn, the current player chooses some number of dice to roll, up to 10. Her turn score is the sum of the dice outcomes, unless any of the dice come up a 1, in which case the score for her turn is only 1 point (the Pig out rule).
To spice up the game, we will play with some special rules:
This project includes six files, but all of your changes will be made to the first one, and it is the only one you should need to read and understand. To get started, download all of the project code as a zip archive.
A starter implementation of Hog. | |
Functions for rolling dice. | |
Utility functions used in the UC Berkeley Class. | |
A graphical user interface for Hog. | |
Tests to check the correctness of your implementation. | |
Utility functions for grading. |
This is a 10 day project. You are strongly encouraged to complete this project with a partner, although you may complete it alone.
Start early! The amount of time it takes to complete a project (or any program) is unpredictable.
You are not alone! Ask for help early and often -- the TAs, lab assistants, and your fellow students are here to help. Try attending office hours or posting on Piazza.
In the end, you and your partner will submit one project. The project is worth 20 points. 17 points are assigned for correctness, and 3 points for the overall composition of your program.
The only file that you are required to submit is hog.py
. You do
not need to modify or turn in any other files to complete the project. To submit
the project, upload your hog.py
file to Gradescope.
For the functions that we ask you to complete, there may be some initial code that we provide. If you would rather not use that code, feel free to delete it and start from scratch, though we higly advise against deleting the skeleton code. You may also add new function definitions as you see fit.
However, please do not modify any other functions. Doing so may result in your code failing our autograder tests. Also, do not change any function signatures (names, argument order, or number of arguments).
A graphical user interface (GUI, for short) is provided for you. At
the moment, it doesn't work, because you haven't implemented the game logic.
Once you finish Problem 4 (the play
function), you will be able to
play a fully interactive version of Hog!
In order to render the graphics, make sure you have Tkinter, Python's main graphics library, installed on your computer. Once you've done that, you can run the GUI from your terminal:
python3 hog_gui.py
Once you're done with Problem 9, you can play against the final strategy that you've created!
python3 hog_gui.py -f
Throughout this project, you should be testing the correctness of your code. It is good practice to test often, so that it is easy to isolate any problems.
Many of the tests are contained within the docstrings of hog.py
.
Additional tests are implemented in hog_grader.py
. To run all tests
until a problem is found, run
python3 hog_grader.py
The command above runs all the tests until an error occurs, at which point it
will stop and print some error messages. You can also run tests for a specific
question with -q
:
python3 hog_grader.py -q 1
Within hog.py
, we've also provided a way to call certain
functions interactively from the terminal:
python3 hog.py -i roll_dice
In the first phase, you will develop a simulator for the game of Hog.
Problem 1 (2 pt). Implement the roll_dice
function in hog.py
, which returns the number of points scored by
rolling a fixed positive number of dice: either the sum of the dice or 1. To
obtain a single outcome of a dice roll, call dice()
. You should
call this function exactly num_rolls
times in your
implementation. The only rule you need to consider for this problem is Pig
out.
As you work, you can add print
statements to see what is
happening in your program. Remove them when you are finished.
Test your implementation before moving on:
python3 hog_grader.py -q 1
You can also run an interactive test, which allows you to type in the dice
outcome, which is helpful for catching cases that are not handled in
hog_grader.py
:
python3 hog.py -i roll_dice
Problem 2 (1 pt). Implement the take_turn
function, which returns the number of points scored for the turn. You will need
to implement the Free bacon rule here. You can assume that
opponent_score
is less than 100. Your implementation should call
roll_dice
.
Test your implementation before moving on:
python3 hog_grader.py -q 2
You can also run take_turn
interactively, which allows you to
choose the number of rolls, the opponent's score, and the result of rolling the
dice.
python3 hog.py -i take_turn
Problem 3 (1 pt). Implement select_dice
, a
helper function that will simplify the implementation of play
(next
problem). The function select_dice
helps enforce the Hog
wild special rule. This function takes two arguments: the scores for the
current and opposing players.
Test your implementation before moving on:
python3 hog_grader.py -q 3
Problem 4 (3 pt). Finally, implement the play
function, which simulates a full game of Hog. Players alternate turns, each
using the strategy originally supplied, until one of the players reaches the
goal
score. When the game ends, play
returns the final
total scores of both players, with Player 0's score first, and Player 1's score
second.
Here are some hints:
select_dice
), as well as the Swine swap special
rule here.take_turn
function that you've
already written.other
. For example, other(0)
evaluates to 1.
strategy0
and strategy1
) takes two
arguments: scores for the current player and opposing player. A strategy
function returns the number of dice that the current player wants to roll
in the turn. Don't worry about details of implementing strategies yet. You
will develop them in Phase 2.Test your implementation before moving on:
python3 hog_grader.py -q 4
You can also run an interactive test, where you can choose how many dice to
roll for both players. You will want to add print
statements to
show the result of playing the game, but be sure to remove them before moving on
to Phase 2.
python3 hog.py -i play
Once you are finished, you will be able to play a graphical version of
the game. We have provided a file called hog_gui.py
that
you can run from the terminal:
python3 hog_gui.py
If you don't already have Tkinter (Python's graphics library) installed, you'll need to install it first before you can run the GUI.
The GUI relies on your implementation, so if you have any bugs in your code, they will be reflected in the GUI. This means you can also use the GUI as a debugging tool; however, it's better to run the tests first.
Congratulations! You have finished Phase 1 of this project!
In the second phase, you will experiment with ways to improve upon the basic strategy of always rolling a fixed number of dice. First, you need to develop some tools to evaluate strategies.
Problem 5 (2 pt). Implement the make_averaged
function. This higher-order function takes a function fn
as an
argument. It returns another function that takes the same number of arguments as
the original. This returned function differs from the input function in that it
returns the average value of repeatedly calling fn
on the same
arguments. This function should call fn
a total of
num_samples
times and return the average of the results.
Note: If the input function fn
is a non-pure function
(for instance, the random
function), then make_averaged
will also be a non-pure function.
To implement this function, you need a new piece of Python syntax! You must write a function that accepts an arbitrary number of arguments, then calls another function using exactly those arguments. Here's how it works.
Instead of listing formal parameters for a function, we write
*args
. To call another function using exactly those arguments, we
call it again with *args
. For example,
>>> def printed(fn): ... def print_and_return(*args): ... result = fn(*args) ... print('Result:', result) ... return result ... return print_and_return >>> printed_pow = printed(pow) >>> printed_pow(2, 8) Result: 256 256
Read the docstring for make_averaged
carefully to understand how
it is meant to work.
Test your implementation before moving on:
python3 hog_grader.py -q 5
Problem 6 (2 pt). Implement the
max_scoring_num_rolls
function, which runs an experiment to
determine the number of rolls (from 1 to 10) that gives the maximum average
score for a turn. Your implementation should use make_averaged
and
roll_dice
. It should print out the average for each possible
number of rolls, as in the doctest for max_scoring_num_rolls
.
Test your implementation before moving on:
python3 hog_grader.py -q 6To run this experiment on randomized dice, call
run_experiments
using the -r
option:
python3 hog.py -r
Running experiments
For the remainder of this project, you can change the implementation ofrun_experiments
as you wish.
By calling average_win_rate
, you can evaluate various Hog
strategies. For example, change the first if False:
to if
True:
in order to evaluate always_roll(8)
against the
baseline strategy of always_roll(5)
. You should find that it loses
more often than it wins, giving a win rate below 0.5.
Some of the experiments may take up to a minute to run. You can always reduce
the number of samples in make_averaged
to speed up experiments.
Problem 7 (1 pt). A strategy can take advantage of the
Free bacon rule by rolling 0 when it is most beneficial to do so.
Implement bacon_strategy
, which returns 0 whenever rolling 0 would
give at least BACON_MARGIN
points and returns
BASELINE_NUM_ROLLS
otherwise (these two global variables
are located right above the always_roll
function).
Test your implementation before moving on:
python3 hog_grader.py -q 7
Once you have implemented this strategy, change run_experiments
to evaluate your new strategy against the baseline. You should find that it
wins more than half of the time.
Problem 8 (2 pt). A strategy can also take advantage of
the Swine swap rule. Implement swap_strategy
, which
BASELINE_NUM_ROLLS
if rolling 0 would cause a harmful
swap that loses points.
BACON_MARGIN
points and roll BASELINE_NUM_ROLLS
otherwise.
Test your implementation before moving on:
python3 hog_grader.py -q 8
Once you have implemented this strategy, update run_experiments
to evaluate your new strategy against the baseline. You should find that it
performs even better than bacon_strategy
, on average.
At this point, run the entire autograder to see if there are any tests that don't pass.
python3 hog_grader.py
Problem 9 (3 pt). Implement final_strategy
,
which combines these ideas and any other ideas you have to achieve a win rate
of at least 0.59 against the baseline always_roll(5)
strategy.
Some ideas:
Note: You may want to increase the number of samples to improve the approximation of your win rate. The course autograder will compute your exact average win rate (without sampling error) for you once you submit your project, and it will send it to you in an email.
You can also play against your final strategy with the graphical user interface:
python3 hog_gui.py -f
The GUI will alternate which player is controlled by you.
Congratulations, you have reached the end of your first project for CS 7!