Axelrod
Axelrod copied to clipboard
Axelrod-Python
K91R Strategy
This is one of the strategies from Axelrod's Second Tournament for which we have the orginal Fortran code.
A description of this strategy is given in Axelrod, R. (1980). More Effective Choice in the Prisoner’s Dilemma. Journal of Conflict Resolution, 24(3), 379-403, where it is known as 'REVISED STATE TRANSITION':
Revised State Transition models the other player as a one-step Markov process. It makes its own choice so as to maximize its own long-term payoff on the assumption that this model is correct.
NOTE:
This description is not sufficient for implementation of the strategy. Analysis of the original Fortran code is required before implementation can be started.
I have a hunch about this one. I might pick it up if no one else wants it.
Oh just my hunch of what the text description is saying.
I'm guessing it's got a simple set of probabilities (either 2 or 4) that get updated based on opponents actions (essentially a reactive or a mem1). Based on that it probably uses closed form expressions for the probabilities ("long term") of states and then on top of that it probably calculates the expected score based on the game value and then decides what to do.
Essentially that's what I would implement based on the text description so happy to wade through :)
