This is the practical material for the Intelligent Systems course, based on the turn based strategy game Planet Wars.
To get to know the concept of the game, please visit Galcon's website. The challenge was inspired by this project and resembles it a lot. (Free multiplayer versions exist for Android and iPhone, but be careful, these are quite addictive).
Your job is to make a bot that will play a turn-based version of this game. General rules about the project, including the rules of the game and the rules of the competition can be found on blackboard.
You require a working python 2.7 environment and a good text editor or an IDE. If that's enough information, read on below. If you're not quite sure how to go about this, see the installation tutorial on Blackboard. There will be a hands-on session in the first week to help you get started.
The rules are encoded in the engine, spefically in the methods moves() and next() of the state object.
Here's a quick summary:
- The aim of the game is to eradicate all planets and ships of the opposing player.
- The two players move one at a time.
- A move is made by sending ships from one planet (the source) to another (the destination).
- A move always results in half the source planet's ships travelling towards the destination.
- A collection of ships in transit is called a fleet.
- If, on arrival, the target planet is neutral (not owned by any player) or owned by the opponent, the fleet attacks the planet: one ship in the fleet cancels out against one ship on the planet. If the fleet has ships left over and the planet doesn't, the fleet's owner takes over ownership of the planet, and the remainder of the fleet becomes stationed at the planet.
- If, on arrival, the target planet is owned by the owner of the fleet, the fleet reinforces the planet: the ships in the fleet are added to those already at the planet.
- Planets occasionally produce ships; the bigger the planet the faster they produce ships. A planet of size 1/n, produces a ship every n turns. The biggest planet size is 1, which produces a ship every turn.
- The standard playing field has size planets. Each player starts with one planet of size 1, at opposite corners of the playing field, cotaining 100 ships. The other four planets are distributed randomly. For the generating code, look at the function State.generate
You will of course also need a working knowledge of python. If you're looking to brush up on your skills, there are many good tutorials available. For instance:
You do not need to be an expert in python to write a functioning bot. If you already know another programming language, you should be able to get going within a day. You'll pick up the details as the project progresses. However, there are a few things that are important to understand. Check if you know what the following mean. If not, take some time to google them and read up:
What happens if I pass a function a 'State' object, and the function changes the object? Do I keep an unchanged state, or does my state change as well?
What's the difference between a class and an object? How are these expressed in python? What does the self keyword do?
Briefly: a method calling itself. Why would this useful, and how does it work?
Advanced python, but they occur occasionally in the code. Useful to know.
Here are some quick use cases and solutions to help you get a feel for the code.
Let 'state' be the state you're given and let's say you want the size of the i'th planet. Then the following a should do the trick:
size_of planet_i = state.planets()[i].size()Or, to print the size of every planet:
for planet in state.planets():
print 'planet {} has size {}.'.format(planet.id(), planet.size())me = state.whose_turn()for i, fleet in enumerate(state.fleets()):
source = fleet.source()
target = fleet.target()
source_crds = source.coords()
target crds = target.coords()
print('Fleet {} is moving from {} to {}'.format(i, source_crds, target_crds))fig = state.visualize() # this is a matplotlib Figure object
fig.savefig('state.png') # matplotlib detects the format you want from the extension you userand_state = State.generate()me = state.whose_turn()
my_planets = state.planets(me)
avg = 0.0
for planet in my_planets:
avg += state.garrison(planet)
avg = avg / len(my_planets)
print('average ships per planet: {}'.format(avg))Our main goal was to write code that was easy to read and to understand. To achieve this, we've made many methods much less efficient than they need to be. This is especially important for a project like this where many of the students are novice programmers. It is also a good principle in general, at least when you write the first version of your code.
You may feel that your bot is to slow with our State and Fleet objects for instance if you're creating an evaluating lots of State objects in a deep minimax tree. Luckily, you're not tied to our API: simply take the State object you're given and copy it to your own, more efficient, implementation. This may get you another plie or two in the search tree, so if you really want to win the competition it might be worth it.
Sure! Just remember this is not a regular project: we've tried to minimize the amount of advanced python, and the number of dependencies. So, it might be that we're aware of the potential improvement, but we haven't used it just to keep the code simple for novice programmers.
The command line scripts provide a convenient starting point, but if you want to do something more complex (like try a range of parameters for your bot), they are probably too limited.
Your best bet is to write your own script that does what you want, and have it call the engine. Have a look at the function play(...) in api/engine.py, or have it run a by itself. See experiment.py for an example.
The codebase has been rewritten entirely, so bots from last year won't work. To reduce overhead, Java is no longer supported, only python.