Using Scenarios

Because most usage of the game will be more or less the same, some stuff has been automated in the form of a Scenario. Scenarios offer a way to define settings and score conditions, and automatically save the results of repeated runs.

For example, we subclass the Scenario module from domination.run:

import domination

class MyScenario(domination.run.Scenario) :
   REPEATS  = 10
   SETTINGS = core.Settings()
   FIELD    = core.FieldGenerator().generate()

   def before_each():
       # Regenerate the field before each game.
       self.FIELD = core.FieldGenerator().generate()

We can now run our scenario and save the results:

ms.one_on_one('agent_one.py', 'agent_two.py', output_folder='results')

Reference

class domination.run.Scenario

A scenario is used to run multiple games under the same conditions.

SETTINGS = Settings()

The settings with which these games will be played

GENERATOR = <domination.core.FieldGenerator object>

Will generate FIELD before each game if defined

FIELD = None

Will play on this field if GENERATOR is None

REPEATS = 2

How many times to repeat each game

SWAP_TEAMS = True

Repeat each run with blue/red swapped

setup()

Function is called once before any games

before_each()

Function that is run before each game. Use it to regenerate the map, for example.

after_each(game)

Function that is run after each game.

Parameters:game – The previous game

classmethod test(red, blue)

Test this scenario, this will run a single game and render it, so you can verify the FIELD and SETTINGS.

Parameters:

• red – Path to red agent
• blue – Path to blue agent

classmethod one_on_one(red, blue, output_folder=None)

Runs the set amount of REPEATS and SWAP_TEAMS if desired, between two given agents.

Parameters:output_folder – Folder in which results will be stored

classmethod tournament(folder=None, agents=None, output_folder=None)

Runs a full tournament between the agents specified, respecting the REPEATS and SWAP_TEAMS settings.

Parameters:

• agents – A list of paths to agents
• folder – A folder that contains all agents, overrides the agents parameter.
• output_folder – Folder in which results will be stored.