#### NAME

eipd - simulate the ecological iterated Prisoner's Dilemma

#### SYNOPSIS

**eipd** **-help**
or
**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***]**

#### DESCRIPTION

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
Defect,'

#### OPTIONS

**-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.

#### PAYOFFS

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

#### MISCELLANY

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-
vant.

#### BUGS

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

#### AUTHOR

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.