Procurar por comparison of agent-based modeling software no wikipedia. Possuem alguma integracao com SIG: AnyLogic, Cormas, Framesticks, MASON, RePast, SeSAM, NetLogo, VisualBoots.

• Hagerstrand's Spatial Innovation Diffusion Model: Earliest known calibrated and validated simulation with implicit “agent based” methodology: Hägerstrand, Torsten (1965) ‘A Monte Carlo Approach to Diffusion’, Archives Européennes de Sociologie, 6(1), pp. 43-67.
• A Neutral Model of Stone Raw Material Procurement: Brantingham, P.J. (2003) A Neutral Model of Stone Raw Material Procurement, American Antiquity 68(3): 487-509.
• Long-term effects of locale occupation and reoccupation in unstrained space: Wandsnider, L. (1992). The spatial dimension of time. In J. Rossignol & L. Wandsnider (Eds.), Space, Time, and Archaeological Landscapes (pp. 257–282). New York: Plenum. Luann Wandsnider is a Professor of Anthropology at the University of Nebraska-Lincoln. The model was written in Borland Turbo Pascal 5.0.
• CATCHSCAPE model - Agent based simulation of a small catchment water management in northern Thailand: Becu N, Perez P, Walker A, Barreteau O, Le Page C. 2003. Agent based simulation of a small catchment water management in northern Thailand. Description of the CATCHSCAPE model. Ecological Modelling 170: 319-331.
• Maine Lobster Fishery - The precursors of governance in the Maine lobster fishery: Wilson J, Yan L, Wilson C. 2007. The precursors of governance in the Maine lobster fishery. PNAS 104(39): 15212-15217.
• LUCIM - Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States: Manson SM and Evans T. 2007. Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States. PNAS 104(52): 20678-20683.
• HELIA - Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States: Manson SM and Evans T. 2007. Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States. PNAS 104(52): 20678-20683.
• The Genetic History of the Iberian Peninsula: A Simulation: Calafell, F., Bertranpetit, J., 1993. The Genetic History of the Iberian Peninsula: A Simulation. Current Anthropology 34, 735–745.
• Discrete Stochastic Models for Traffic Flow: Schreckenberg, M. and Schadschneider, A. and Nagel, K. and Ito, N. (1995) “Discrete stochastic models for traffic flow.” Physical Review E 51 (4): 2939-2949. DOI: 10.1103/PhysRevE.51.2939
• SOME (Sluce's Original Model for Exploration): Brown, Daniel G., Page, Scott E., Riolo, Rick, Zellner, Moira, and William Rand (2005) “Path dependence and the validation of agent-based spatial models of land use.” International Journal of Geographical Information Science, Special Issue on Land Use Dynamics 19(2): 153-174
• GEOSim: Cederman L-E 2003 “Modelling the size of wars: from billiard balls to sand piles”, American Political Science Review, 97(1), 135-150 Would be great if a Netlogo version would be available. A Repast version is mentioned at http://gisagents.blogspot.com/2006/05/repast-model-of-week-geosim.html
• Escape Panic: Helbing, D., I. Farkas & T. Vicsek (2000) Simulating dynamical features of escape panic, Nature 407, 487-490. There is code available via http://angel.elte.hu/panic/ but it would be great to have a Netlogo version available.

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

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

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.