Classifying the new strategy¶
Every strategy class has a classifier dictionary that gives some classification of the strategy according to certain dimensions. Some of the classifiers have formulas that try to compute the value for different strategies. Where these exist, they’re overridden by the values defined in this dictionary. When creating a new strategy, you should try to fill out all of the dictionary.
Let us take a look at the dimensions available by looking at
>>> import axelrod >>> classifier = axelrod.TitForTat.classifier >>> for key in sorted(classifier.keys()): ... print(key) inspects_source long_run_time manipulates_source manipulates_state memory_depth stochastic
You can read more about this in the Classification of strategies section but here are some tips about filling this part in correctly.
Note that when an instance of a class is created it gets it’s own copy of the
default classifier dictionary from the class. This might sometimes be modified by
the initialisation depending on input parameters. A good example of this is the
>>> joss = axelrod.FirstByJoss() >>> boring_joss = axelrod.FirstByJoss(p=1) >>> axelrod.Classifiers["stochastic"](joss) True >>> axelrod.Classifiers["stochastic"](boring_joss) False
A classifier value defined on the instance overrides the value defined for the class.
There are currently three important dimensions that help identify if a strategy obeys axelrod’s original tournament rules.
inspects_source- does the strategy ‘read’ any source code that it would not normally have access to. An example of this is
manipulates_source- does the strategy ‘write’ any source code that it would not normally be able to. An example of this is
manipulates_state- does the strategy ‘change’ any attributes that it would not normally be able to. An example of this is
These dimensions are currently relevant to the obey_axelrod function which checks if a strategy obeys Axelrod’s original rules.