Hello,
I'm trying to use the library of strategies to infer a strategy from a dataset with paired matches of plays. Is there a way to pass a list of plays to a strategy from the library (other than manually using the axelrod.Human(name="me")?
For example, I have a dataset of a person's plays by round (C, D, D, C...) and the adversary's list of plays as well (D,C,D,C,D...). I'd like to know if the person's strategy matched TFT, TF2T, etc. I have an R script that does this manually for a small number of strategies, but re-coding every strategy has become cumbersome!
Ideally, I could just pass both to a script, but if I can just pass the adversary's plays to a for loop of the strategies in the library, I can use another mechanism to compare that output to my dataset of human plays. Thanks for any help in advance!
It's been a while, but I think you could set up a MockPlayer(actions=adversary_actions_as_Axelrod.Action.C_or_D). or use Cycler(cycle=string_of_Cs_and_Ds). create a player list with this player first. create a Tournament with edges=[(0, 1), (0, 2) ... (0, len(player_list) - 1)]. that makes every passed in strategy play only the first one. see which results match your expected outcome.
this might be an example of what you want?:
https://github.com/Axelrod-Python/Axelrod/blob/master/axelrod/fingerprint.py#L237
v4.6.0 released with a number of small fixes, final remaining strategy from Axelrod's first tournament and a new history class: https://github.com/Axelrod-Python/Axelrod/releases/tag/v4.6.0
axl.RevisedDowning(revised=False)
axl.Downing(revised=True),
Might be interesting to note that TFT does win the second tournament, reproducibly, despite coding errors in the initial tournament
Yup will do!
Lastly, an FYI: you used x A x^T in the replicator equation, which is is fine if A is symmetric I think, but note that it's more common to use x^T A x
Sure although I believe this is just a question of convention on x being in or
Regarding the reproduction of axelrods first tournament (if it's still an issue):
In the original tournament, the strategies did not only play against each other but also a match against themselves. The latter is not the case using the tournament.play()-function. You can try this by playing a small tournament using TitForTat, Defector, Cooperator and Grudger. This is a tournament you can easily calculate by hand. The result using tournament.play() is:
players = [axl.Cooperator(), axl.Defector(), axl.TitForTat(), axl.Grudger()]
tournament = axl.Tournament(players)
results = tournament.play(progress_bar=False)
ranked = results.ranked_names # ranked list of strings of players
scores_per_turn = np.sort(np.mean(results.normalised_scores, axis=1)) # sorted list of mean scores
scores_per_turn = scores_per_turn[::-1] # reverse; now it is in ranked order
print('Ranked Players:\t',ranked)
print('Scores per turn:',scores_per_turn)Output:
Ranked Players: ['Defector', 'Tit For Tat', 'Grudger', 'Cooperator']
Scores per turn: [2.34666667 2.33166667 2.33166667 2. ]This corresponds exactly to the strategies playing against each other but not against themselves. If they also played against themselves, the ranking would be T4T, Grudger (same score as T4T) , Cooperator, Defector.
I tried using a complete graph with additional edges from one node to itself, but that didn't work either.
[((0, 0),
{'turns': 200,
'game': Axelrod game: (R,P,S,T) = (3, 1, 0, 5),
'noise': 0,
'prob_end': None,
'match_attributes': None},
10),
((0, 1),
{'turns': 200,
'game': Axelrod game: (R,P,S,T) = (3, 1, 0, 5),
'noise': 0,
'prob_end': None,
'match_attributes': None},
10),
((1, 1),
{'turns': 200,
'game': Axelrod game: (R,P,S,T) = (3, 1, 0, 5),
'noise': 0,
'prob_end': None,
'match_attributes': None},
10)]results = tournament.play(progress_bar=True, filename="tournament.csv")