eipd - simulate the ecological iterated Prisoner's Dilemma


       eipd -help
       eipd   [-steps integer] [-rounds integer] [-seed  integer]
              [-CC double] [-CD double] [-DC double] [-DD double]
              [-Iallc  double]  [-Itft  double]  [-Irand  double]
              [-Ipav   double]   [-Ialld  double]  [-rcp  double]
              [-noise double]


       The ecological iterated Prisoner's  Dilemma  is  simulated
       over time according to the specified parameters.  At every
       time step the population of each strategy is calculated as
       a  function  of  the  expected  scores  earned against all
       strategies weighted by the populations of  the  opponents.
       Possible  strategies  include  'Always Cooperate,' 'Always


       -steps integer
              Number of steps to simulate.

       -rounds integer
              Number of rounds per step.

       -seed integer
              Random seed for initial state.

       -CC double
              Reward Payoff.

       -CD double
              Sucker Payoff.

       -DC double
              Temptation Payoff.

       -DD double
              Punish Payoff.

       -Iallc double
              Initial population of All-C.

       -Itft double
              Initial population of TFT.

       -Irand double
              Initial population of Random.

       -Ipav double
              Initial population of Pavlov.

       -Ialld double
              Initial population of All-D.

       -rcp double
              Probability of C for Random strategy.

       -noise double
              Probability of noise.


       The payoff matrix for the Prisoner's Dilemma game is  usu-
       ally expressed as:
                                 Player B's Move
            Player A's Move | cooperate |  defect   |
                | cooperate |  CC, CC   |  CD, DC   |
                |    defect |  DC, CD   |  DD, DD   |

       where  the  table entries are (A's payoff, B's payoff) and
       CC, CD, DC, and DD are the reward, sucker, temptation, and
       punish payoffs, respectively.  For each of these four out-
       comes you will probably want the payoffs  to  reflect  the

            (DC > CC > DD > CD) and ((CD + DC) / 2 < CC).


       random noise (via the -noise option) manifests itself as a
       cell making a randomly selected move in  a  single  round.
       In  this  case,  both the cell whose action was altered as
       well as that cell's opponents "remember" what  the  random
       move was on the next round.

       During  each time step, every strategy plays against every
       other strategy as well as against itself.

       The initial population levels for all strategies  will  be
       normalized, so the scaling of the option values is irrele-


       No sanity checks are performed to make sure  that  any  of
       the options make sense.


       Copyright (c) 1997, Gary William Flake.

       Permission  granted  for any use according to the standard
       GNU ``copyleft'' agreement provided that the author's com-
       ments  are  neither  modified nor removed.  No warranty is
       given or implied.

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