11(2):2

11(2):7 10(1):9 9(4):R-J 9(4):R-B 9(1):3 8(3):7 8(2):8 7(3):1

András Németh and Károly Takács (2007) The Evolution of Altruism in Spatially Structured Populations http://jasss.soc.surrey.ac.uk/10/3/4.html

Abstract: […] Here we examine the evolution of […] altruism with a focus on altruistic teaching. Teaching is modeled as a knowledge transfer which enhances the survival chances of the recipient, but reduces the reproductive efficiency of the provider. […]

for (every living_agent x):
  if (random(1000) < innovation_rate) x.knowledge:=1;
  if ((x.teacher) && (x.knowledge=1)):
    repeat // search for an agent without knowledge
      if (proximity_based) y := random_agent_in_proximity
      else y := random_agent;
    until (y.knowledge = 0)
  if (y.learning)
    y.knowledge := 1;
    x.breeading_chance := x.breeading_chance - costs;
  end if
end for

David Hales (2002) Group Reputation Supports Beneficent Norms http://jasss.soc.surrey.ac.uk/5/4/4.html

Abstract: This paper demonstrates the role of group normative reputation in the promotion of an aggression reducing possession norm in an artificial society. […]

LOOP 50 times
  Select an agent (A) at random from the population (with replacement)
  Activate agent - (agent (A) selects and executes one action):
   IF appropriate - receive reputational information from all neighbours
   IF current cell contains food then
      IF food prepared then {EAT-FOOD}
      IF food picked-up then {PREPARE-FOOD}
      IF food not-picked-up then {PICKUP-FOOD}
   END IF
   IF free food item is visible in neighbourhood {MOVE} to food item.
   IF a food item can be smelled two cells away then {MOVE} towards it.
   IF an agent holds a food item one cell away in neighbourhood then
     IF current strategy allows then {ATTACK}
   END IF
   IF any neighbouring cells are free then select one at random and {MOVE}
   No other actions are possible so {PAUSE}
END LOOP

Derek Gatherer (2002) Identifying cases of social contagion using memetic isolation: comparison of the dynamics of a multisociety simulation with an ethnographic data set http://jasss.soc.surrey.ac.uk/5/4/5.html

Abstract: A simulation is presented of a grid of connected societies of reproducing agents. These agents are capable of horizontal and vertical transmission of non-genetic cultural traits (memes). […]

INITIALIZATION:
  For each of the 100 cells in the 10-by-10 array:
  {
    place two Agents in each cell
    randomly assign one of four Gene attributes to each individual
    randomly assign one of four Meme attributes to each individual
  }
ITERATION:
  For 100 generations do the following:
  {
    For each Agent:
    {
      If Agent Meme attribute = "A" and CultSel = "Y"
      {
        Double parameters n and o for that agent
      }
      If Agent Meme attribute = "A" and NatSel = "Y"
      {
        Double parameter r for that agent
      }
      If a random number x < r
      {
        Reproduce Agent
      }
      If a different random number y < o
      {
        If same random number y is also < n
        {
          Transmit Meme to any Agent in any adjacent cell
        }
        else
        {
          Transmit Meme to any Agent in same cell
        }
      }
      If a different random number z < m
      {
        Migrate Agent to adjacent cell
      }
    }
  }
END.